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IEEE Transactions on Aerospace and Electronic Systems
Journal Prestige (SJR): 0.611
Citation Impact (citeScore): 3
Number of Followers: 319  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9251
Published by IEEE Homepage  [228 journals]
  • IEEE Aerospace and Electronic Systems Society Information

    • Free pre-print version: Loading...

      Pages: C2 - C2
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • On the Design of RIS–UAV Relay-Assisted Hybrid FSO/RF
           Satellite–Aerial–Ground Integrated Network

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      Authors: Thang V. Nguyen;Hoang D. Le;Anh T. Pham;
      Pages: 757 - 771
      Abstract: Satellite–aerial–ground integrated network (SAGIN) has been widely envisioned as a promising network architecture for 6G. In the SAGINs, high-altitude platform (HAP)-aided relaying satellite systems using hybrid free-space optics (FSO)/radio-frequency (RF) communications have recently attracted research efforts worldwide. Nevertheless, the main drawback of hybrid FSO/RF systems is the restricted bandwidth of the RF connection, especially when the FSO one is blocked by cloud coverage. This article explores a novel solution for the hybrid FSO/RF HAP-based SAGIN under the impact of weather and atmospheric conditions. Specifically, an additional unmanned aerial vehicle (UAV) is deployed to diverse the FSO link from the HAP-to-ground station to avoid cloud blockage while maintaining a high-speed connection of the FSO link. A mirror array constructed by reconfigurable intelligent surface (RIS), an emerging technology, is mounted on the UAV to reflect the signals from the HAP. The channel model of RIS–UAV takes into account both atmospheric turbulence and hovering-induced pointing errors. Furthermore, we present a novel link switching design with a multirate adaptation scheme for the proposed network under different weather and turbulence conditions. Numerical results quantitatively confirm the effectiveness of our proposal. Additionally, we provide insightful discussions that can be helpful for the practical system design of RIS–UAV-assisted HAP-based SAGIN using hybrid FSO/RF links. Monte Carlo simulations are also performed to validate the accuracy of theoretical derivations.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Deep-Learning Hopping Capture Model for Automatic Modulation
           Classification of Wireless Communication Signals

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      Authors: Lin Li;Zhiyuan Dong;Zhigang Zhu;Qingtang Jiang;
      Pages: 772 - 783
      Abstract: Recent years have witnessed a surge of developments in deep learning (DL) motivated by a variety of contemporary applications. The conventional DL-based automatic modulation classification (AMC) methods are always relying on a great quantity of data. In this article, we propose a DL-based AMC model with short data for the spectrum sensing of wireless communication signals. First, a hopping transform unit is proposed to represent the transient variation occurred either by frequency, amplitude, or phase modulations. Second, a bidirectional long short-term memory-based hopping feature perception model, namely deep-learning hopping capture model (DHCM), is built for the AMC. A comprehensive comparison of the DHCM with other existing methods is then provided under various signal-to-noise ratios. The experimental results demonstrate the superiority of the proposed method under short data.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Distributed Adaptive Fault-Tolerant Formation Control for Heterogeneous
           Multiagent Systems With Communication Link Faults

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      Authors: Jianye Gong;Bin Jiang;Yajie Ma;Zehui Mao;
      Pages: 784 - 795
      Abstract: In this article, we investigate the distributed adaptive fault-tolerant formation control problem for a group of heterogeneous multiagent systems consisting of multiple follower unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with parametric uncertainties and communication link faults. Based on the local states information of the vehicles, the adaptive fault-tolerant formation control protocol with varying control gains is developed for each follower UAV and UGV such that all followers track the dynamic trajectory of the virtual leader and obtain the expected formation configuration simultaneously under the influence of communication link faults and external disturbances. The distributed formation tracking convergence performance is discussed through Lyapunov theory. Finally, a simulation study based on the UAVs–UGVs collaborative systems is provided to show the effectiveness of the developed control strategy.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Target Recognition in Single-Channel SAR Images Based on the
           Complex-Valued Convolutional Neural Network With Data Augmentation

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      Authors: Ruonan Wang;Zhaocheng Wang;Kewen Xia;Huanxin Zou;Jun Li;
      Pages: 796 - 804
      Abstract: In recent years, with the rapid development of deep learning theory, real-valued convolutional neural networks (CNNs) have achieved significant success in the field of synthetic aperture radar (SAR) target recognition. However, different from natural images, the SAR images have complex information due to their special imaging mechanism. Traditional deep learning methods for SAR target recognition only employ the amplitude information and ignore the phase portion, which may sacrifice some useful information in the original complex SAR data. Moreover, the number of samples of SAR images is very limited. This is undoubtedly a huge challenge for the traditional real-valued CNNs which require numerous labeled data for training. Especially, since the single-channel SAR image contains only one channel, it has less available information than the multiple-channel SAR image. To deal with the above problems, a complex-valued CNN, for target recognition in single-channel SAR images is proposed in this article. The amplitude and phase information in the complex SAR data are fully utilized for target recognition. In addition, to alleviate the problem of small samples, this article also proposed a data augmentation method based on the complex SAR images. The experimental results based on the measured SAR data demonstrate that the proposed algorithm has better performance than the traditional real-valued CNNs.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • A Successive Interference Cancellation-Based Receiver for Secondary
           Surveillance Radar

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      Authors: Francois Le Neindre;Guillaume Ferre;Dominique Dallet;Frankie Letellier;Kevin Pitois;
      Pages: 805 - 816
      Abstract: Secondary surveillance radar communications, which purpose is to acquire aircrafts critical information, are on the brink of spectrum saturation. This is the result of dense traffic and different waveforms modulation schemes, used in Modes A/C and Mode S communication layers, which share the same unscheduled propagation bandwidth. This leads to a significant rise of packet collision probability. In this context, we propose an original single-channel receiver able to process the simultaneous reception of several Mode A/C and S packets. The decoding strategy relies on the successive interference cancellation principle, comprising original detection, decoding, and reconstruction processes. The relevance of our proposition is validated by numerical simulation and confirmed through field experiments on automatic dependent surveillance-broadcast signals reception.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • The Pose Estimation of the Aircraft on the Airport Surface Based on the
           Contour Features

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      Authors: Daoyong Fu;Songchen Han;Wei Li;Hanren Lin;
      Pages: 817 - 826
      Abstract: The pose estimation of the aircraft in the taxiing or parking state on the airport surface has been proved helpful for the level of control and command, operation efficiency, capacity of handling special situations of the airports. However, current methods cannot provide satisfied estimate results of the pose of aircrafts because they regard the aircraft as a point. To solve the pose estimation problem of the aircrafts, especially for the small-sized ones, this article proposes an aircraft pose estimation method based on the contour features. First, the contour features of the aircraft are utilized to design a 2-D pose skeleton to show the pose information of the aircraft on the ground. Second, the flux is adopted to represent the two-dimensional aircraft pose skeleton. Finally, a two-branch convolutional neural network is designed to estimate aircraft pose including the aircraft skeleton detection and the aircraft orientation estimation. To overcome the lack of a benchmark dataset, an aircraft dataset was built, and the evaluation of the proposed method's performance on this dataset was also carried out. The experimental results show that our proposed method has satisfied performance compared with other state-of-art approaches on the airport surface aircraft dataset.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Micro-Doppler Separation Based on U-Net and Plot-Curve Association for
           Ballistic Target

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      Authors: Degui Yang;Xing Wang;Zhenghong Peng;Liang Hu;Jin Li;
      Pages: 827 - 836
      Abstract: The high-precision separation of micro-Doppler (m-D) curves is the key to micromotion feature extraction and parameter estimation for ballistic target in midcourse. The m-D curves of each scatter overlap seriously in the time–frequency domain and are also affected by nonideal scattering phenomena such as strong noise and occlusion effects, which poses a significant challenge to the traditional curve separation methods. Aiming at this problem, a m-D curve separation algorithm under nonideal scattering conditions is proposed in this article. First, the m-D curve and noise are separated through the U-Net model in the time–frequency domain. Then, on the basis of eliminating the effect of redundant and pseudoplots by plot condensation and plot processing, the m-D plots are associated and regrouped based on interpolation and curve smoothness function. Finally, the effectiveness and robustness of the proposed algorithm have been illustrated by extensive simulation experiments.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • On the Nondata-Aided Maximum Likelihood Phase Error Detectors for 16- and
           32-APSK

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      Authors: Michael Rice;Nathan Jensen;Laura Landon;Bryan Redd;Autumn Twitchell;
      Pages: 837 - 850
      Abstract: The nondata-aided maximum likelihood phase error detectors (PEDs) for use in phase-lock loops (PLLs) for 16-APSK and 32-APSK are derived and analyzed. The derivation focuses on a numerically stable expression for the PED output as a function of the derotated matched filter input. The analysis focuses on the S-curve, phase ambiguity, and phase error variance. The 16-APSK PED S-curve exhibits 12 lock points (a 12-fold phase ambiguity) and, when used in a PLL, produces a phase error variance better than commonly used alternatives and achieves its theoretical lower bound at a lower signal-to-noise ratio than the alternatives. The 32-APSK PED S-curve exhibits 16 (low signal-to-noise ratio) or 20 (high signal-to-noise ratio) lock points (a 16- or 20-fold phase ambiguity) and, when used in a PLL, produces a phase error variance better than commonly used alternatives and achieves its theoretical lower bound at a lower signal-to-noise ratio than the alternatives. It is proved that the two PEDs converge to their corresponding decision-directed PEDs as signal-to-noise ratio increases.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • A 15-V Tolerant and Radiation-Hardened MOSFET Driver With Positive and
           Negative References

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      Authors: Xin Lei;Xingguo Gao;Jun Deng;Zhou Shu;Fang Tang;
      Pages: 851 - 857
      Abstract: Radiation-hardened and high-voltage power circuits are key components in aerospace applications. However, when working at high voltages, the effects of the total ionizing dose (TID) and the single event limit the application of power driving circuits in a radiation environment. A 15-V tolerant radiation-hardened MOSFET driver is designed. The circuit architecture, which is based on positive and negative references, can reduce the gate source voltage of the transistors to less than 5 V, allowing the selection of thin gate oxide high-voltage transistors. On this basis, adopting enclosed layout transistor (ELT) N-channel metal oxide semiconductor (NMOS) transistors help the driver to obtain a good resilience to TID hardness. In addition, this work optimizes the layout of high-voltage N-type laterally diffused metal oxide semiconductor transistors in the driver to effectively improve the single-event burnout (SEB) threshold. Three chips with different N-type drift region lengths are designed and fabricated in a 0.35-$mu text{m}$ bipolar-CMOS-DMOS (BCD) process. The test results show that the TID hardening capability of these chips with zener references and ELT NMOS transistors all exceeded 100 krad (Si). In addition, this driver is tested under heavy ion irradiation with linear energy transfer exceeding 75 MeV$cdot mathrm{{c}}{mathrm{{m}}^{2}}mathrm{{/mg}}$. The results show that this driver with a 6.6-$mu text{m}$ drift region length has no single-event latch-up, single-event gate rupture, or SEB sensitivity.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Robust Output-Feedback Predictive Control for Proximity Eddy Current
           Detumbling With Constraints and Uncertainty

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      Authors: Xiyao Liu;Haitao Chang;Panfeng Huang;Zhenyu Lu;
      Pages: 858 - 870
      Abstract: Proximity operation can significantly improve the efficiency of eddy current detumbling. However, the tumbling motion and noncooperation of space debris make the chaser execute collision avoidance maneuvers and be influenced by model uncertainty. In this article, an inertial-oriented safety corridor is proposed by taking the debris' angular momentum as the central axis, which can avoid the frequent collision maneuvers of the chaser. Meanwhile, a desired detumbling trajectory under this safety corridor is designed to detumble the angular velocity of space debris. Then, a robust output-feedback controller considering safety corridor and model uncertainty is proposed by combining moving horizon estimation (MHE) and model predictive control (MPC). The MHE is employed to estimate the system state and model uncertainty which is compensated by a feedforward control law. Furthermore, the MPC without terminal ingredients is designed to realize the optimal performance of fuel consumption and the robust tracking stability of the system. Finally, taking the Chinese Sinosat-2 satellite as the simulation case, the effectiveness of the proposed scheme is verified.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • General Design Method for Two-Dimensional Multicorrelator Antimultipath
           Tracking Loop for BOC Signals

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      Authors: Yunhan Qi;Zheng Yao;Mingquan Lu;
      Pages: 871 - 885
      Abstract: As binary offset carrier signals are widely used in global navigation satellite systems, tracking ambiguity threats and multipath become two main factors that affect ranging precision. 2-D tracking loops, such as double estimate tracking and double-phase estimator, estimate the code delay and subcarrier delay by the delay locked loop and the subcarrier locked loop, respectively, to obtain high precision and unambiguous propagation delay. Although 2-D tracking techniques can effectively alleviate the impact of tracking ambiguity threats, their antimultipath performance has not been improved compared with one-dimensional tracking techniques. This article proposes a general design method for 2-D multicorrelator antimultipath tracking (TMAT) structures based on heuristic optimization. Compared with 2-D tracking loops equipped with traditional antimultipath structures, such as narrow early minus late and double delta structures, TMAT structures designed for different signals with different bandwidths always have better multipath mitigation performance without any degradation of tracking robustness. According to case studies, because of the great antimultipath improvement of TMAT structures, the slight degradation in thermal noise performance can be acceptable. Also, the designed TMAT structures are insensitive to the relative amplitude of multipath and bandwidth of signals, indicating the great practicality of this technique.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Interactional Influence Analysis of DC Bus Voltage Versus Servo Systems
           and Stabilization Technology for Aerospace Combined Power Supply Systems

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      Authors: Cheng Qiu;Hangyu Li;Zhenkun Song;Jing Huang;Lu Feng;Xiangyang Wang;
      Pages: 886 - 896
      Abstract: With rapid developments in aerospace science and technology, higher requirements are being placed on the control accuracy of aircraft. As the power source of aircraft servo systems, the power quality of the combined power supply system directly affects the control accuracy of aircraft. Therefore, it is crucial to improve the performance of this combined power supply system. In this article, a method based on nonsingular terminal sliding mode control (NTSMC) is proposed to suppress the DC bus voltage fluctuation of the combined power supply system, which is caused by servo motor loads. First, the mutual influences of the servo motor running state and the DC bus voltage on one another are analyzed. Then, the mathematical model of the DC bus voltage regulation module, based on a bidirectional DC-DC converter and ultracapacitor, is established. The NTSMC algorithm is adopted, and the sliding mode surface and control law are designed to suppress the DC bus voltage fluctuation of the combined power supply system. Finally, simulation and experimental research are carried out to verify the effectiveness of the method. The results show that the proposed method can effectively suppress the fluctuation of DC bus voltage, and that NTSMC is superior to the traditional PID control method for aerospace combined power supply systems.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • A Robust TSWLS Localization of Moving Target in Widely Separated MIMO
           Radars

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      Authors: Mohammad Reza Jabbari;Mohammad Reza Taban;Saeed Gazor;
      Pages: 897 - 906
      Abstract: In this article, we investigate the target localization problem in a multiple input multiple output radar systems with widely separated antennas. We derive an accurate and robust closed-form estimator for the target's location and velocity by using the well-known two-stage weighted least squares technique. We define the nuisance variables in the first stage to obtain a set of pseudo-linear equations and solve them by the WLS estimator. We then approximate the nuisance variables with the first-order Taylor series around the estimates from the previous stage in order to reformulate a set of linear equations, which is solved again using the WLS estimator. Unlike the state-of-the-art methods, the proposed method is robust against the presence of incorrect Doppler shift measurements and perturbations errors imposed by the linear approximations. Simulation results demonstrate that our method outperforms the state-of-the-art methods not only in performance and complexity, but also in robustness.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Tensor-Based Sparse Recovery Space-Time Adaptive Processing for Large Size
           Data Clutter Suppression in Airborne Radar

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      Authors: Ning Cui;Kun Xing;Zhongjun Yu;Keqing Duan;
      Pages: 907 - 922
      Abstract: Sparse recovery space-time adaptive processing (SR-STAP) can achieve an ideal clutter suppression with very few training samples, however, its application faces two challenges: 1) severe gird mismatch effect and 2) large time-resources requirement. In practice, a coarse space-time grids will bring a serious mismatch between the true clutter points and the divided grids, which leads to a significant performance degradation of clutter suppression. Although the high-resolution mesh can effectively reduce the grid mismatch effect, its cost is huge computational load. Thus, it is meaningful to reduce the large-scale dictionary operation complexity while maintaining suboptimal clutter suppression performance for SR-STAP when applying in real airborne radar system. This article proposed a tensor-based SR-STAP scheme aims at large-scale dictionary application. In the proposed framework, traditional vector-based operations are replaced by their corresponding low-complexity tensor representation. As a result, a large-scale matrix operation can be degraded into multiple small-scale matrix calculation, thus the huge computational loading can be saved in recovery. A comparison of tensor-based SR-STAP and traditional vector-based SR-STAP in large-scale dictionary application is also exhaustive discussed here. Based on this framework, a tensor-based sparse Bayesian learning and its fast matrix-realization form are developed. A series of carefully designed numerical simulation and measurement experiments indicate that the significant advantages of the tensor-based SR-STAP whether in performance or computation loading.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Reconfiguration Optimization of Relative Motion Between Elliptical Orbits
           Using Lyapunov-Floquet Transformation

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      Authors: Xue Bai;Meili Huang;Ming Xu;Jizhong Liu;
      Pages: 923 - 936
      Abstract: This article investigates the reconfiguration optimization of the formation flying in elliptical orbits. Based on the Tschauner–Hempel equations, the time-varying system has been reduced to a time-independent one by Lyapunov–Floquet transformation without losing its relative motion characteristics. A geometric configuration invariant of the formation is introduced and general relative configurations are considered as linear combinations of essential components in proportion to this invariant. Benefitting from the evolution of the configuration invariant, the reconfiguration optimization is converted into an optimal parameter selection problem and the transfer trajectory is parameterized by a functional integral. In particular, the indirect method of optimal control based on the reduced dynamics avoids the time-varying derivative of costate variables, which simplifies the optimization problem. The numerical results of both low-thrust and impulsive reconfigurations verify the effectiveness of the reconfiguration optimization based on the reduced relative dynamics.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • ChiNet: Deep Recurrent Convolutional Learning for Multimodal Spacecraft
           Pose Estimation

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      Authors: Duarte Rondao;Nabil Aouf;Mark A. Richardson;
      Pages: 937 - 949
      Abstract: This article presents an innovative deep learning pipeline, which estimates the relative pose of a spacecraft by incorporating the temporal information from a rendezvous sequence. It leverages the performance of long short-term memory units in modeling sequences of data for the processing of features extracted by a convolutional neural network (CNN) backbone. Three distinct training strategies, which follow a coarse-to-fine funneled approach, are combined to facilitate feature learning and improve end-to-end pose estimation by regression. The capability of CNNs to autonomously ascertain feature representations from images is exploited to fuse thermal infrared data with electrooptical red–green–blue inputs, thus mitigating the effects of artifacts from imaging space objects in the visible wavelength. Each contribution of the proposed framework, dubbed ChiNet, is demonstrated on a synthetic dataset, and the complete pipeline is validated on experimental data.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Radar High-Speed Target Coherent Detection Method Based on Modified Radon
           Inverse Fourier Transform

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      Authors: Kai Xiong;Guanghui Zhao;Guangming Shi;
      Pages: 950 - 962
      Abstract: Within the long-time coherent integration (CI) in radar detection, the range walk effect inevitably impacts high-speed targets, which makes coherent detection methods invalid. To address this problem, a coherent detection method, a modified radon inverse Fourier transform (MRIFT), was developed in this article. The MRIFT can estimate velocity via single parameter searching and achieve the target's CI in the 2-D frequency domain using the inverse Fourier transform. Compared with the traditional coherent detection methods, the MRIFT achieved great detection performance and range and velocity estimation performance and averted the blind speed side lobe effect at a lower computational cost. Simulations demonstrate the effectiveness and efficiency of the proposed MRIFT.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Disturbance Observer-Based Constrained Attitude Control for Flexible
           Spacecraft

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      Authors: Mehdi Golestani;Weidong Zhang;Yunxiang Yang;Nguyen Xuan-Mung;
      Pages: 963 - 972
      Abstract: This article investigates the difficult issue of fixed-time constrained attitude control for a flexible spacecraft under the influence of the system uncertainties, environmental disturbance, and abrupt actuator faults. The contributions of the proposed control framework are twofold. First, an observer is presented to precisely reconstruct the uncertain dynamics within a fixed time regardless of the initial estimation error while the settling time is given as a specific parameter. Second, using a combination of prescribed performance control (PPC) and barrier Lyapunov function approaches, a simple structure constrained attitude control for flexible spacecraft is proposed while desired performance specifications for both quaternion and rotation velocity are indirectly achieved by constraining the sliding manifold. A distinctive feature of the suggested control framework is that the settling time of the closed-loop system is finite and explicitly expressed as two tunable gains even when abrupt actuators faults happen. Numerical simulations substantiate the ability of the offered control to effectively accomplish favorable attitude maneuver under the negative effect of the inertia matrix uncertainty, external disturbances, flexible structures vibration, and actuators faults.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Distributed Robust Kalman Filters Under Model Uncertainty and
           Multiplicative Disturbance

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      Authors: Xingkai Yu;Jianxun Li;
      Pages: 973 - 988
      Abstract: This article considers the problem of distributed robust state estimation for sensor networks in the presence of model uncertainty and multiplicative noise. More precisely, we assume that the modeling uncertainty, i.e., the actual state space model belongs to an ambiguity set or a set of convex polytopic uncertain parameters. Several robust Kalman filters are proposed based on projection theorem, variance-constrained optimization, and robust mean square error estimation with different types of ambiguity sets. Stability analysis and simulation example verify the presented distributed robust filters.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Deep ToA Mask-Based Recursive Radar Pulse Deinterleaving

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      Authors: Haoran Xiang;Furao Shen;Jian Zhao;
      Pages: 989 - 1006
      Abstract: In a complex electromagnetic environment, multiple radar signals of various modes are densely interleaved. In this environment, radar parameters overlap seriously and change continuously over time. Traditional radar pulse deinterleaving algorithms face severe challenges, such as parameters missing, pulse jitter, and the increasing number of electronic countermeasure devices. In this article, we propose a recursive deinterleaving algorithm based on blind signal separation and deep learning to cope with such a situation. The recursive deinterleaving network (RDN) of deep ToA mask (DTM) maps the ToA train to a suitable feature space first. ToA coefficient masks of each radar emitter are estimated with the local and global context information of the radar pulse feature. Then, the RDN sorts out several radar pulse trains recursively with the help of dual-path attention. It also predicts the number of emitters with nearly 100% accuracy and handles the unknown pulse repetition interval (PRI) situation. More accurate pulse deinterleaving results can be obtained if the DTM utilizes more radar parameters through proper preprocessing fine-tuning and postprocessing reclustering. The processing steps of the DTM are introduced in detail. The simulation shows that it can achieve 97% sorting accuracy for multipulse interleaved radar train with jitter PRI and pulse missing. The DTM algorithm can also deal with the interleaved radar signals of different PRI modulations by reclustering with noisy PDW information. On the premise of knowing the modulation type or PRI information, the pulse train deinterleaving accuracy of multimodulation emitters is higher.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • MIMO Radar Transmit Beampattern Shaping for Spectrally Dense Environments

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      Authors: Ehsan Raei;Saeid Sedighi;Mohammad Alaee-Kerahroodi;M. R. Bhavani Shankar;
      Pages: 1007 - 1020
      Abstract: Designing unimodular waveforms with a desired beampattern, spectral occupancy, and orthogonality level is of vital importance in the next-generation multiple-input multiple-output (MIMO) radar systems. Motivated by this fact, in this article, we propose a framework for shaping the beampattern in MIMO radar systems under the constraints simultaneously ensuring the unimodularity, desired spectral occupancy, and orthogonality of the designed waveform. In this manner, the proposed framework is the most comprehensive approach for MIMO radar waveform design focusing on beampattern shaping. The problem formulation leads to a nonconvex quadratic fractional programming. We propose an effective iterative to solve the problem, where each iteration is composed of a semidefinite programming followed by eigenvalue decomposition. Some numerical simulations are provided to illustrate the superior performance of our proposed over the state of the art.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • MIMO Radar Robust Waveform-Filter Design for Extended Targets Based on
           Lagrangian Duality

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      Authors: Zhou Xu;Jiahua Zhu;Zhuang Xie;Chongyi Fan;Xiaotao Huang;
      Pages: 1021 - 1036
      Abstract: In this article, we address the robust waveform-filter design problem for extended targets with a colocated multiple-input–multiple-output radar. The goal is to maximize the worst-case signal-to-interference-pulse-noise ratio (SINR) at the receiver against the uncertain target impulse response (TIR) with the peak-to-average ratio constraint imposed on the waveform, which results in a nonconvex minimax optimization problem. Two kinds of uncertainty sets for the TIR, namely, the spherical set and the annular set, are considered. Combing the duality theory in optimization and the semidefinite relaxation (SDR) technique, we devise the Lagrangian duality semidefinite relaxation (LDSDR) and the Lagrangian duality double SDRalgorithms to tackle the associated waveform-filter design problems against the spherical and the annular sets, respectively. The convergences of the proposed algorithms are proved theoretically. Numerical results verify the effectiveness of the proposed algorithms. Compared with the current algorithms for the spherical set, the proposed LDSDR algorithm achieves the highest worst-case SINR with a reduced computational complexity.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Inbound Carrier Plan Optimization for Adaptive VSAT Networks

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      Authors: Clement Lacoste;Wallace A. Martins;Symeon Chatzinotas;Luis D. Emiliani;
      Pages: 1037 - 1050
      Abstract: The past decades witnessed the application of adaptive coding and modulation (ACM) in satellite links. However, ACM technologies come at the cost of higher complexity when designing the network's carrier plan and user terminals. Accounting for those issues is even more important when the satellite link uses frequencies in Ka band and above, where the attenuation caused by tropospheric phenomena is a major concern. In this article, we propose a solution for the inbound, i.e., return link, carrier plan sizing of very small aperture terminal networks. As tropospheric attenuation is a key factor, we present a mathematical problem formulation based on spatially correlated attenuation time series. Our proposed sizing scheme is formulated as a mixed integer linear programming optimization problem. The numerical results for a test scenario in Europe show a 10 to 50% bandwidth improvement over traditional sizing methods for outage probabilities lower than 1%.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Composite Adaptive Control for Anti-Unwinding Attitude Maneuvers: An
           Exponential Stability Result Without Persistent Excitation

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      Authors: Xiaodong Shao;Qinglei Hu;Daochun Li;Yang Shi;Bowen Yi;
      Pages: 1051 - 1066
      Abstract: This article provides an exponential stability result for the adaptive anti-unwinding attitude tracking problem of a rigid body with uncertain inertia parameters, without the need for a persistent excitation (PE) condition. Specifically, a composite adaptive control scheme with guaranteed parameter convergence is proposed by integrating the dynamic regressor extension and mixing (DREM) technique into the dynamically scaled immersion and invariance adaptive control framework, wherein we modify the scaling factor so that the algorithm design does not involve any dynamic gains. To avoid the unwinding problem, a barrier function is introduced as the attitude error function, along with the establishment of two key algebraic properties for exponential stability analysis. Aiding by a linear time-varying filter, the scalar regressor of DREM is extended to generate an exciting counterpart. In this manner, the derived controller is shown to permit closed-loop exponential stability under a strictly weaker interval excitation condition than PE, in the sense that both the output-tracking and parameter estimation errors exponentially converge to zero. Furthermore, the composite adaptive law is also augmented to achieve finite-/fixed-time parameter convergence in a time-synchronized manner. Simulation results are presented to verify our theoretical findings.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Online Trajectory Replan for Gliding Vehicle Considering Terminal Velocity
           Constraint

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      Authors: Youngil Kim;Namhoon Cho;Jongho Park;Youdan Kim;
      Pages: 1067 - 1083
      Abstract: Controlling the terminal velocity can improve the effectiveness of guided missiles. In particular, a ballistic missile propelled by solid rocket motors can successfully accomplish its mission when it hits the target at an appropriate speed. In this study, a method for modifying the trajectory of gliding vehicle, i.e., gliding ballistic missiles, is proposed to meet the terminal velocity constraint by reflecting the effects of the environment during a flight. The proposed framework consisting of trajectory generation and dynamic propagation compensates for errors due to uncertainties in real time. The trajectory generation step provides various trajectories that satisfy the given constraints based on information about the current state. The dynamic propagation step efficiently predicts the terminal velocity for each of the generated trajectories and finds the trajectory with the lowest terminal speed error. A numerical simulation is performed considering various conditions to demonstrate the performance of the proposed method.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Energy Management for an All-Electric Aircraft via Optimal Control

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      Authors: Mengyuan Wang;Suryanarayana Kolluri;Krishna Shah;Venkat R. Subramanian;Mehran Mesbahi;
      Pages: 1084 - 1095
      Abstract: In this article, we develop an integrated approach to energy optimization for an all-electric aircraft. Our approach involves the formulation of the aircraft energy optimization as a set of optimal control problems (OCPs)—integrating battery and flight dynamics—for the cruise and climb phases, as well as the complete flight profile. The corresponding OCPs are then examined in the context of Pontryagin's minimum principle, providing necessary optimality conditions for the proposed integrated approach. Our analysis is then followed by utilizing the numerical solver Tomlab to devise computational solutions for the energy optimization OCPs. We then proceed to characterize the performance of the energy-optimal solutions for distinct models of the battery. In particular, we show that the choice of the battery model does not alter the form of optimal control for the flight system; however, the current profiles for the battery pack and the total operating costs are affected by the adopted models used for optimization. Finally, we develop a Simulink model built around physics-based battery dynamics to further characterize the interplay between aircraft energy operating costs and the underlying battery dynamics.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Noncooperative LEO Satellite Orbit Determination Based on Single Pass
           Doppler Measurements

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      Authors: Ruofan Deng;Honglei Qin;Haotian Li;Danyao Wang;Hongli Lv;
      Pages: 1096 - 1106
      Abstract: Precise orbit information is the premise of the wide application of low-Earth-orbit (LEO) satellites. Traditional orbit determination (OD) methods have disadvantages of poor reliability, high hardware cost, and long OD time. To account for these issues, we propose an OD framework, using several distributed facilities to acquire Doppler shift values of signals of opportunity (SOPs) during the same pass. First, we propose a search-least squares (LS) algorithm for initial orbit determination (IOD), providing a reliable accurate initial value for precise orbit determination (POD). Moreover, a nonrecursive cubature batch filter (NR-CBF) is proposed for POD to reduce linearization errors, avoid tuning parameters, and save the calculation time. Besides, we modify the measurement model by considering signal propagation delays and provide the corresponding theoretical basis. Finally, the real experiment result verifies the feasibility of the proposed method, whose velocity accuracy is at m/s grade.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Co-Pulsing FDA Radar

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      Authors: Wanghan Lv;Kumar Vijay Mishra;Shichao Chen;
      Pages: 1107 - 1126
      Abstract: Target localization based on frequency diverse array (FDA) radar has lately garnered significant research interest. A linear frequency offset (FO) across FDA antennas yields a range–angle-dependent beampattern that allows for the joint estimation of range and direction of arrival. Prior works on the FDA largely focus on the one-dimensional linear array to estimate only azimuth angle and range while ignoring the elevation and Doppler velocity. However, in many applications, the latter two parameters are also essential for target localization. Furthermore, there is also an interest in radar systems that employ fewer measurements in temporal, Doppler, or spatial signal domains. We address these multiple challenges by proposing a coprime L-shaped FDA, wherein coprime FOs are applied across the elements of L-shaped coprime array, and each element transmits at a nonuniform coprime pulse repetition interval (C-Cube). This co-pulsing FDA yields a significantly large number of degrees of freedom (DoFs) for target localization in the range–azimuth–elevation–Doppler domain while also reducing the time on target and the transmit spectral usage. By exploiting these DoFs, we develop a C-Cube autopairing (CCing) algorithm, in which all the parameters are ipso facto paired during a joint estimation. We show that the C-Cube FDA requires at least $2sqrt{Q+1}-1$ antenna elements and $2sqrt{Q+1}-1$ pulses to guarantee the perfect recovery of $Q$ targets as against $Q+1$ elements and $Q+1$ pulses required by both the L-shaped uniform linear array and the L-shaped linear FO FDA with uniform pulsing. We derive Cramér–Rao bounds (CRBs) for joint angle–range–Doppler estimation errors for the C-Cube FDA and provide the conditions under which the CRBs exist. Numerical experiments with our CCing algorithm show great performance improvements in parameter recovery, wherein the C-Cube radar achieves at least 15% higher target hit rate with shorter-dwell time than its uniform counterparts.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Optimization of Safety Critical IFR Helicopter Trajectories in Alpine
           Areas Using MILP

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      Authors: Evelyn Weiss;Sébastien Guillaume;Alain Geiger;Roland Hohensinn;Heinz Wipf;
      Pages: 1127 - 1138
      Abstract: Currently, helicopter operations according to Instrument Flight Rules consist of high-altitude trajectories where the probability of collision with terrain is assumed to be very low. In such high altitudes, the risk of icing has to be considered; additionally, the flight time is unnecessarily long. Therefore, this article elaborates on an optimization approach to finding helicopter trajectories minimizing both flight time and height above terrain. To ensure safe operations, an isoprobability surface is calculated using collision probabilities, representing a surface above which the probability of collision with terrain is smaller than a chosen safety level. The optimization problem is solved using Mixed Integer Linear Programming. To evaluate the resulting trajectories the time until collision is evaluated for each waypoint, using a time-to-go approach based on Monte Carlo simulations. The optimization with MILP yields feasible trajectories fulfilling a chosen safety level. Although the approach is computationally expensive, it serves as a basis for further research on these kinds of trajectory optimization applications.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Dynamic Reallocation Model of Multiple Unmanned Aerial Vehicle Tasks in
           Emergent Adjustment Scenarios

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      Authors: Jun Tang;Xi Chen;Xiaomin Zhu;Feng Zhu;
      Pages: 1139 - 1155
      Abstract: Due to their strong risk tolerance, low manufacturing cost, and good maneuverability, unmanned aerial vehicles (UAVs) have been widely used in various fields. Among related challenges, coordinated task assignment is a key scientific issue for autonomous control of UAVs. In this article, based on the idea of fuzzy C-means clustering and the ant colony optimization algorithm, a cooperative multiple task reallocation problem with target precedence constraints for heterogeneous UAVs is proposed. The contributions of this research are the performance evaluation of the original algorithms in a dynamic context, consideration of changes in some attributes of the environment, and the extension of these algorithms to properly address more realistic dynamic emergent adjustment scenarios. According to the corresponding task reallocation strategy, the scenarios are divided into three categories: the complete redistribution strategy can effectively cope with scenarios where tasks have changed significantly, the partial adjustment strategy can induce partial responses to the changes of individual tasks, and group redistribution can effectively solve the problem of task target threat rating changes. The simulation results show that the dynamic reallocation model of multi-UAV tasks in dynamic emergent adjustment scenarios can achieve better performance to complete the corresponding tasks based on the proposed scheme. In addition, we deployed the developed graphical modeling and analysis software platform to implement the dynamic reallocation model of multi-UAV tasks in dynamic emergent scenarios, and the validity and reliability of the proposed task reallocation model were verified.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Adaptive Fuzzy Control for a Spatial Flexible Hose System With Dynamic
           Event-Triggered Mechanism

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      Authors: Zhijie Liu;Jun Shi;Yakun He;Zhijia Zhao;Hak-Keung Lam;
      Pages: 1156 - 1167
      Abstract: In this study, we develop an adaptive boundary control strategy with a dynamic event-triggered mechanism (dETM) for an aerial refueling hose system involving certain performance specifications. The controller uses the barrier Lyapunov function (BLF) method, where the introduction of two boundary deflection transformations, an asymmetric scaling function, and a behavior-shaping function reduces the complexity of the stability analysis and guarantees that the system meets the required performance description. Fuzzy logic systems (FLSs) are developed to strengthen the adaptivity in other unmodeled dynamics. Particularly in this work, the dETM is constructed to decrease the unnecessary signal transmission between the controllers and actuators while achieving vibration suppression. The stability of the controlled systems is proved via Lyapunov analysis. Finally, we establish numerical simulations to illustrate the validity of the designed controllers.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Distributed Control of 6-DOF Leader-Following Multispacecraft Formation
           Near an Asteroid Based on Scaled Twistors

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      Authors: Bo Zhang;Jing Chen;Binxing Hu;
      Pages: 1168 - 1182
      Abstract: This article addresses the distributed six-degree-of-freedom control problem of translation-rotation coupled spacecraft formation in the vicinity of an asteroid. Due to the complicated gravity field, there exist no circular or elliptic orbits for the spacecraft, which renders the control schemes designed for the spacecraft formation near the Earth inapplicable. In the framework of twistors, a distributed leader-following control scheme is proposed by combining the dynamic surface technique and consensus theory under an undirected communication topology. First, a scaled-twistor-based position-attitude coupled dynamic model of the spacecraft near an asteroid is established to circumvent numerical difficulty. Since the state of the leader can only be accessed by a subset of the followers, an observer is integrated into the control scheme to estimate the state of the leader for each follower. Then, the pose error between each follower and its desired pose is represented by the scaled twistor. Based on the error dynamics, virtual control is designed according to the consensus theory, and a distributed control law is proposed via the dynamic surface method. To eliminate the large control effort and aggressive transient in the initial phase, adaptive gains are introduced into the control scheme. Furthermore, neural networks are used to compensate for not only the external disturbances, but also the filtering errors resulting from the dynamic surface method. The stability of the closed-loop system is proven via Lyapunov theory, and numerical simulations are carried out to demonstrate the effectiveness of the proposed control scheme.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Undersampled Ionospheric Irregularity Threat Parameterization Using a
           Three-Dimensional Model for Satellite-Based Augmentation Systems

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      Authors: Eugene Bang;Jiyun Lee;
      Pages: 1183 - 1201
      Abstract: Single-frequency Satellite-based Augmentation Systems (SBASs) compute and broadcast estimates of vertical ionospheric delays and integrity bounds on the estimates called the Grid Ionospheric Vertical Errors (GIVEs) at Ionospheric Grid Points (IGPs). The dominant contribution of the GIVE comes from the undersampled ionospheric irregularity threat model. This article presents a methodology for the undersampled ionospheric threat parameterization to reduce the magnitude of the GIVE. A threat model metric that measures the uniformity of angular separation of measurements was designed and incorporated into the current metric set, the fit radius, and the relative centroid metric (RCM), such that threat geometries were parameterized rigorously based on the extended metric set. An undersampled threat model was constructed with the proposed three-dimensional metric set and historical ionospheric storm data from the Global Navigation Satellite System stations in South Korea. We also simulated SBAS availability in the Korean region to demonstrate the benefit of the presented threat model methodology. In our preliminary assessment, the implementation of the proposed method was found to improve the 99.9% availability of the approach procedure with vertical guidance I by up to 12% when the approach was applied to the GIVE monitor algorithm.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Distributed Online Learning for Coexistence in Cognitive Radar Networks

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      Authors: William W. Howard;Anthony F. Martone;R. Michael Buehrer;
      Pages: 1202 - 1216
      Abstract: This work addresses the coexistence problem for radar networks. Specifically, we model a network of cooperative, independent, and non-communicating radar nodes which must share resources within the network as well as with non-cooperative nearby emitters. We approach this problem using online Machine Learning (ML) techniques. Online learning approaches are specifically preferred due to the sequential nature of the problem. For this task we specifically select the multi-player multi-armed bandit (MMAB) model, where each radar node in a network makes independent selections of center frequency and waveform with the same goal of improving tracking performance for the network as a whole. For accurate tracking, each radar node communicates observations to a fusion center on set intervals. The fusion center has knowledge of the radar node placement, but cannot communicate to the individual nodes fast enough for waveform control. Each independent and identical node must choose one of many waveforms to transmit in each Pulse Repetition Interval (PRI) while avoiding collisions with other nodes and interference from the environment. The goal for the network as a whole is to minimize target tracking error, which relies on obtaining high SINR in each time step. Our contributions include a mathematical description of the MMAB framework adapted to the radar network scenario. We conclude with a simulation study of several different network configurations. Experimental results show that iterative, online learning using MMAB outperforms the more traditional sense-and-avoid (SAA) and fixed-allocation approaches.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Feasible Sequential Convex Programming With Inexact Restoration for
           Multistage Ascent Trajectory Optimization

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      Authors: Yangyang Ma;Binfeng Pan;Rui Yan;
      Pages: 1217 - 1230
      Abstract: This article presents a feasible sequential convex programming method to solve the multistage ascent trajectory optimization problem. The proposed method is based on the inexact restoration technique, in which a more feasible intermediate iterate is first produced by solving a constrained least-squares problem, and then a more optimal iterate is generated by solving a convex programming problem constructed around the newly found feasible solution. By virtue of the inexact restoration idea, the proposed method prevents the common artificial infeasibility issue and can provide the intermediate iterate as a feasible suboptimal solution if the algorithmic procedure terminates before convergence. In addition, the Picard iteration-based convexification and Chebyshev polynomial-based discretization methods are employed in the proposed method, given their benefits in terms of robustness, efficiency, and solution accuracy. Numerical simulations for a minimum-time launch ascent problem are conducted, and the results show that the proposed method exhibits better practical performance than other sequential convex programming methods.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Inhomogeneity Suppression CFAR Detection Based on Statistical Modeling

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      Authors: Xinbiao He;Yanwei Xu;Minggang Liu;Chengpeng Hao;
      Pages: 1231 - 1238
      Abstract: An inhomogeneity suppression constant false alarm rate detector (IS-CFAR) based on statistical modeling is proposed for inhomogeneous sonar or radar data. First, the inhomogeneous background is modeled and classified based on ordered statistics. Then, the background power is estimated based on the different group of data according to the model of the inhomogeneous background. Finally, the IS-CFAR is designed to improve the detection performance for inhomogeneous sonar or radar data. Simulation results show that the IS-CFAR detector can suppress the background inhomogeneity and improve the CFAR detection performance under inhomogeneous background.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Passivity-Based Model Predictive Control for Tethered Despin of Massive
           Space Objects by Small Space Tug

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      Authors: Junjie Kang;Zheng H. Zhu;
      Pages: 1239 - 1248
      Abstract: In this article, we study the stable control of tethered despin of a massive rotating space object in a central gravity field by a small space tug. A control scheme under the passivity-based model predictive control framework is designed to ensure that the constraints of state and input (bounded libration angle, positive tether tension, and bounded thrust) are satisfied. Furthermore, an additional passivity constraint is introduced into the passivity-based model predictive control to guarantee the asymptotic stability of the closed-loop control system. The attainable equilibrium configuration of the tethered system is first analyzed. Then, a framework of the storage energy function is constructed by the potential energy shaping methodology to establish the passivity mapping of the tethered system from input to output. Finally, the strictly asymptotic stability of despinning control of the tethered system under the proposed control law is theoretically proved by the invariance theorem and Lyapunov stability theory. The effectiveness of the proposed control scheme is verified by numerical simulation.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Deep Neural Network Correlators for GNSS Multipath Mitigation

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      Authors: Haoqing Li;Parisa Borhani-Darian;Peng Wu;Pau Closas;
      Pages: 1249 - 1259
      Abstract: Machine learning and, more precisely, data-driven models are providing solutions where physics-based models are intractable. This article discusses the use of deep learning models to characterize the intricate effects of multipath propagation on GNSS correlation outputs. Particularly, we aim at substituting standard correlation schemes, optimal under single-ray Gaussian noise assumptions, with neural network (NN)-based correlation schemes, that are able to learn the otherwise challenging to model multipath channels. The article shows that deep neural networks (DNNs), as applied to tracking loops, can provide enhanced performance as compared to standard correlation schemes in 1) line-of-sight (LOS) scenarios, by filtering out more noise thanks to strong prior regularization through knowledge of correlation characteristics and Gaussian noise during training process; and 2) at the same time, the DNN can adjust its behavior to better disentangle multipath signals from LOS signals. This article provides results showing the superiority of the proposed DNN trained models, with focus on time-delay tracking in a variety of realistic scenarios.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Minimum-Time Trajectory Generation of eVTOL in Low-Speed Phase:
           Application in Control Law Design

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      Authors: Mingkai Wang;Nana Chu;Pranav Bhardwaj;Shuguang Zhang;Florian Holzapfel;
      Pages: 1260 - 1275
      Abstract: With the emergence of electric propulsive technologies in the past decades, electric vertical takeoff and landing (eVTOL) aircraft gain increasing interest, which paves the path for advanced air mobility. However, there is insufficient prior knowledge and historical data for performance assessment of eVTOL, especially in the low-speed performance analysis, which is critical for operational safety and efficiency. To this end, this article utilizes trajectory optimization to provide a baseline reference for control design. An algorithm is proposed to generate the minimum-time trajectory of eVTOL. To guarantee computational efficiency, motion primitives are derived based on abstracted equations of motion. Thereafter, the possible types of optimal trajectories are discussed regarding mission scenarios and verified by the direct collocation method. The potential application of the proposed method is showcased in the design optimization of the reference model for control law. The results show that the optimized reference model reduces control resource consumption and improves transient behaviors of eVTOL aircraft.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Integrated Guidance and Gimbal Control for Coverage Planning With
           Visibility Constraints

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      Authors: Savvas Papaioannou;Panayiotis Kolios;Theocharis Theocharides;Christos G. Panayiotou;Marios M. Polycarpou;
      Pages: 1276 - 1291
      Abstract: Coverage path planning with unmanned aerial vehicles (UAVs) is a core task for many services and applications including search and rescue, precision agriculture, infrastructure inspection and surveillance. This work proposes an integrated guidance and gimbal control coverage path planning (CPP) approach, in which the mobility and gimbal inputs of an autonomous UAV agent are jointly controlled and optimized to achieve full coverage of a given object of interest, according to a specified set of optimality criteria. The proposed approach uses a set of visibility constraints to integrate the physical behavior of sensor signals (i.e., camera-rays) into the coverage planning process, thus generating optimized coverage trajectories that take into account which parts of the scene are visible through the agent's camera at any point in time. The integrated guidance and gimbal control CPP problem is posed in this work as a constrained optimal control problem which is then solved using mixed integer programming (MIP) optimization. Extensive numerical experiments demonstrate the effectiveness of the proposed approach.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Efficient Hierarchical Signature Scheme With Batch Verification Function
           Suitable for ADS-B System

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      Authors: Peng Yi;Jiguo Li;Yichen Zhang;Yu Chen;
      Pages: 1292 - 1299
      Abstract: The federal aviation administration has ruled that starting January 1, 2020, all aircraft flying over the United States must be equipped with an automatic dependent surveillance-broadcast (ADS-B) system to broadcast aircraft location information. The plaintext communication between the ADS-B system and the ground transmission tower is extremely vulnerable to interception and tampering by criminals. In addition, because of the increasing volume of airport air traffic, the airport tower is unable to quickly and efficiently verify large numbers of aircraft from all over the world. To address these issues, a three-level hierarchical signature scheme with a batch verification function suitable for the ADS-B system is proposed. Based on the computational Diffie–Hellman assumption, we prove that the proposed scheme is secure against existing unforgeability. Futhermore, we show the advantages of our scheme in computational cost through experiments.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Effect of Componential Camouflage on Aircraft's IR Multiband
           Susceptibility

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      Authors: Juyeong Nam;Taehwan Kim;Namkyu Lee;Injoong Chang;Hyung Mo Bae;Kyungsu Park;Hyung Hee Cho;
      Pages: 1300 - 1311
      Abstract: Aircraft's infrared (IR) signature modeling considering thermal-flow characteristics and emissivity control for IR camouflage have been recently studied. However, there are few studies trying to analyze the camouflage effect by applying IR camouflage material to the aircraft surface based on the surface temperature distributions or to find suitable surfaces for effective camouflage. In this article, we describe the effect of componential signature reduction on aircraft's susceptibility to IR-guided missiles considering multiband detection. We analyzed the thermal-fluid characteristics of aircraft using coupled simulations of computational fluid dynamics with a conduction and radiation solver. We calculated IR signature levels from the surface temperature distribution in the mid-wavelength (3–5 μm) and long-wavelength (8–12 μm) bands for the multiband susceptibility analysis. Based on the surface temperature distribution and IR signature level, the aircraft surface was classified according to surface temperature and heating cause. Consequently, we determined that the zone highly heated by the external flow or plume has the dominant impact on the IR signature. We expect that this article will be helpful for advancing and realizing IR camouflage in actual flight conditions.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Possibility Generalized Labeled Multi-Bernoulli Filter for Multitarget
           Tracking Under Epistemic Uncertainty

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      Authors: Han Cai;Jeremie Houssineau;Brandon A. Jones;Moriba Jah;Jingrui Zhang;
      Pages: 1312 - 1326
      Abstract: This article presents a flexible modeling framework for multitarget tracking based on the theory of outer probability measures. The notion of labeled uncertain finite set is introduced and utilized as the basis to derive a possibilistic analog of the $delta$-generalized labeled multi-Bernoulli ($delta$-GLMB) filter, in which the uncertainty in the multitarget system is represented by possibility functions instead of probability distributions. The proposed method inherits the capability of the standard probabilistic $delta$-GLMB filter to yield joint state, number, and trajectory estimates of multiple appearing and disappearing targets. Beyond that, it is capable to account for epistemic uncertainty due to ignorance or partial knowledge regarding the multitarget system, e.g., the absence of complete information on dynamical model parameters (e.g., probability of detection, birth) and initial number and state of newborn targets. The features of the developed filter are demonstrated using two simulated scenarios.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Enhanced and Generalized Coprime Array for Direction of Arrival Estimation

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      Authors: Junpeng Shi;Fangqing Wen;Yongxiang Liu;Zhen Liu;Panhe Hu;
      Pages: 1327 - 1339
      Abstract: Owing to the large degrees of freedom and reduced mutual coupling by generating difference coarrays, nonuniform linear arrays have aroused great interest in direction of arrival estimation. Previous works have shown some improved sparse arrays, while few find the common features hidden within these structures. In this article, we define a generic-coarray concept to reveal the impacts of variable ranges and element spacing on the uniform degrees of freedom (uDOFs), by which the sufficient condition for the connected coarrays is derived. We then propose an enhanced and generalized coprime array (EGCA) structure from the generic-coarray perspective. We show that the closed-form expression for the range of uDOFs is a function of sensor numbers and interelement spacing. We prove that, by coarray extension and hole filling, the optimized EGCA possesses more uDOFs than the previous coprime arrays. Furthermore, EGCA also provides the minimum number of sensor pairs with small separation. Simulations verify the superiority of EGCA using the subspace-based algorithm.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Robust Distributed Sensor Fault Detection and Diagnosis Within Formation
           Control of Multiagent Systems

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      Authors: Yujiang Zhong;Youmin Zhang;Shuzhi Sam Ge;Xiao He;
      Pages: 1340 - 1353
      Abstract: This article investigates the fault detection and diagnosis (FDD) problem for multiagent systems subject to sensor faults and disturbances. A distributed proportional integral derivative formation control protocol is constructed to achieve practical formation. A distributed FDD scheme, comprised of a fault detection module, a fault isolation module, and a fault estimation module, is designed within the formation control. For fault detection, the relationship between residuals and sensor faults in the multiagent systems is established such that each agent can detect the faults of all agents. For fault isolation, the distributed observer in each agent can determine whether the fault is in itself or its neighbors. Utilizing the absolute output information of each agent and the relative output information among neighboring agents, a distributed fault estimator is derived to provide the fault magnitude information. Simulation results are presented to demonstrate the effectiveness of the proposed FDD scheme.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Three-Dimensional Biased Proportional Navigation Guidance Based on Spatial
           Rotation of Predicted Final Velocity

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      Authors: Namhoon Cho;Seokwon Lee;Hyo-Sang Shin;Tae-Hun Kim;
      Pages: 1354 - 1370
      Abstract: This article presents the design of 3-D biased proportional navigation guidance laws for arrival at a stationary target along a desired direction based on the spatial rotation of the predicted final velocity vector. The focus is on full constructive derivation using vector-form expressions without introducing the local representation of rotation, such as Euler angles or quaternions. The proposed approach synthesizes the bias command in the form of an angular velocity vector through the realization of the predictive control design philosophy, the direction that has been unexplored in a 3-D setting. The proposed approach avoids heuristic choices and approximations in the design process and, hence, overcomes the limitation of earlier studies. The vector-form design approach provides theoretical and practical advantages, including rigor in derivation, clear geometric understandings about the problem provided by identification of the most effective direction for rotation of final velocity, independence from the selection of a fixed coordinate system, avoidance of singularities in local representations, more direct trajectory shaping, and simple implementation.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • A Payoff Augmentation Approach to Two Pursuers and One Evader Inertial
           Model Differential Game

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      Authors: Yiqun Zhang;Pengfei Zhang;Xiaodong Wang;Feng Song;Chaoyong Li;
      Pages: 1371 - 1381
      Abstract: In this article, we study the two-on-one inertial model pursuit-evasion differential game with a payoff augmentation approach. In particular, the pursuit-evasion game is treated as a deadline game, and its payoff function is augmented to eliminate the deadline as well as to facilitate a more sophisticate model. In addition, we introduce the retrogressive path for analytical solution to the equilibrium strategy for the closed-loop game, and proceed to demonstrate that the closed-loop game can be converted to a one-side optimization problem for the evader, with the help of the augmented payoff function, under an open-loop Stackelberg strategy. More specifically, we establish the conditional equivalency between the open-loop solution and the closed-loop one. Simulation results verify the effectiveness of the proposed strategy.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Integrating Covariance Intersection Into Bayesian Multitarget Tracking
           Filters

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      Authors: Daniel E. Clark;Mark A. Campbell;
      Pages: 1382 - 1391
      Abstract: Multitarget tracking systems typically provide sets of estimated target states as their output. It is challenging to be able to integrate these outputs as inputs to other tracking systems to gain a better picture of the area under surveillance since they do not conform to the standard observation model. Moreover, in cyclic distributed systems, there may be common information between state estimates that would mean that fused estimates may become overconfident and corrupt the system. In this article, we develop a Bayesian multitarget estimator based on the covariance intersection algorithm for multitarget track-to-track data fusion. The approach is integrated into a multitarget tracking algorithm and demonstrated in simulations. The approach is able to account for missed tracks and false tracks produced by another tracking system.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Randomized Low-Rank and Sparse Decomposition-Based Receiver Search
           Strategy for Electronic Support Receivers

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      Authors: İsmail Gül;Işın Erer;
      Pages: 1392 - 1399
      Abstract: Narrow bandwidth electronic support (ES) receivers have higher sensitivity than wide bandwidth ES receivers. However, to intercept the emitting signals in a wide spectrum range, the frequency spectrum should be swept over time. Hence, a scanning strategy has to be used. Mostly, the strategy is determined based on prior information about possible threats. Hence, there is a lack of robustness to determine the best scanning strategy. With using only the prior information, the policies cannot model a closed-loop system. These types of strategies are insufficient to use the advantage of previously gathered data. At this point, we propose a method to determine the scanning strategy of the frequency spectrum, which learns each emitting signal pattern by using transformed predictive state representations. This method benefits from the recent advances in a rank minimization problem using the GoDec algorithm and allows us to use low-rank and also sparse component to predict the best possible frequency band. With this method, time consumption of the most hotspot part of the recursive process, the subspace identification part is decreased around 80$%$, and also better average radar detection ratio are achieved.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Wind-Tolerant Event-Based Adaptive Sliding-Mode Control for VTOL
           Rotorcrafts Multiagent Systems

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      Authors: Jonatan Uziel Alvarez-Muñoz;Juan Antonio Escareno;Jeremy Chevalier;Steven Daix;Ouiddad Labanni-Igbida;
      Pages: 1400 - 1410
      Abstract: The present article investigates the consensus control of a multiagent system (MAS) composed by vertical take-off and landing (VTOL) rotorcrafts subject to aerodynamic disturbances. Initially, the attitude's VTOLs model based on quaternion formalism is detailed to subsequently derive the corresponding control law. Likewise, the MAS translational dynamics is extended to entail the airframe's aerodynamics. In order to achieve the consensus objective, a robust adaptive event-triggered sliding-mode control (SMC) is synthesized considering a leader–follower scheme guaranteeing Lyapunov's closed-loop stability and avoiding the Zeno behavior. Results from an extensive simulation stage witness the effectiveness of the proposed control scheme. The latter allows to fulfill the collective consensus and leader's trajectory tracking objectives in presence of unknown disturbances while keeping a reduced computational cost.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Flush Air Data Sensing Based on Dimensionless Input and Output Neural
           Networks With Less Data

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      Authors: Yang Liu;Chen-an Zhang;Xunshi Yan;Wen Liu;
      Pages: 1411 - 1425
      Abstract: Neural networks have the ability to deal with the flush air data sensing (FADS) system of various vehicles. However, the demand for large quantities of training data limits its application. To overcome the problem, this article develops a FADS algorithm called dimensionless input and output neural networks FADS (DIO-NNFADS) to estimate air data states. The DIO-NNFADS is utilized to approximate the aerodynamic model defined by dimensional analysis, which decouples the freestream static pressure. Thus, trained by less data from a single flight profile, the DIO-NNFADS can achieve good accuracy in the entire flight envelope, effectively reducing the training data for neural networks. The Mach number, angle of attack, angle of sideslip, and the pressure coefficients are directly output by the DIO-NNFADS. And the static pressure and dynamic pressure are solved by the equations composed of the measured pressures and pressure coefficients. The proposed FADS algorithm is verified on a simplified supersonic model through numerical simulation. Results show that the algorithm can estimate the Mach number within the relative error of 2.9%, static pressure and dynamic pressure within the relative error of 6.2%, and the angle of incidence within the absolute error of 0.4$^circ$ in the entire flight envelope. Besides, the optimal size of the training data set for the DIO-NNFADS is discussed. Furthermore, the influence of port layout and selection is analyzed, and the algorithm also shows good performance for a port layout without stagnation point.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Automatic Carrier Landing Control With External Disturbance and Input
           Constraint

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      Authors: Yang Yuan;Haibin Duan;Zhigang Zeng;
      Pages: 1426 - 1438
      Abstract: In this article, the automatic carrier landing problem of the unmanned aerial vehicle (UAV) is studied, where external disturbance and input constraint are considered. Deck motion prediction is necessary in classical automatic carrier landing system (ACLS), which is difficult to compensate precisely due to the motion is primarily stochastic. Thus, a relative motion model between the UAV and ideal glide path is established, by which the disturbance of the wave to the carrier is regarded as external disturbance to the model as well as the airwake to the UAV, and the problem of trajectory tracking is transformed into a stabilization problem. Moreover, nonsingular fast terminal sliding mode observer is designed to estimate disturbance, and it is proved that observed error can converge to residual in fixed time. In addition, an ACLS based on backstepping control structure is proposed, where input constraint is considered, and the closed-loop control system is proved to be stable by the Lyapunov function. Finally, numerical simulations are performed to demonstrate reliability and superiority of the proposed ACLS.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Satellite Formation Flying Control by Using Only Angle Measurements

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      Authors: Jianqing Li;Liangming Chen;Ming Cao;Chaoyong Li;
      Pages: 1439 - 1451
      Abstract: This article investigates a practical formation control problem of multisatellite system, in which a group of small satellites are required to reach and maintain a desired geometric configuration under communication and measurement constraints. Toward this goal, we consider each satellite uses its local coordinate system and senses its neighboring satellites to obtain angle measurements. A formation control scheme using only the angle measurements is proposed to form the desired configuration. Moreover, the triangular and polygonal configuration cases are considered, in which the sum of interior angles of polygons being a constant is utilized to guarantee the stability of the determined final configuration. In particular, motivated by formation rigidity principles which mean that satellites' formation is seen as a multipoint framework that needs to be rigid to guarantee the uniqueness of the shape, we propose a formation determination approach to construct a rigid square configuration and prove that, compared with existing schemes, the inter-satellite relative positions and the knowledge of the communication topology are not needed for the proposed formation control law. Moreover, since the angle measurements are scalars and sensed with respect to the local coordinate system, the proposed angle-based formation control law is more robust against the misalignment on satelltes' coordinate systems. Simulation results are presented to illustrate the performance of the proposed control laws.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Accurate and Computational-Efficient Analytical Solutions for the Extended
           Two-Step Magnetometer Calibration

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      Authors: Rogério Paes Menezes Filho;Felipe Oliveira e Silva;Gustavo de Souza Carvalho;
      Pages: 1452 - 1467
      Abstract: One of the biggest challenges involving low-cost inertial and magnetic sensors, especially the latter, is the inherent distortion/corruption of their measurements by systematic errors. Such errors can be so compromising that using the corrupted measurements for navigation purposes becomes an impossible task. In addition to sensor fusion, which aims at improving performance, calibration techniques can precisely estimate these errors, which, then, can be compensated for. This article revisits the problem of in-field magnetometer calibration, focusing on the traditional and well-established ellipsoid fitting-based extended two-step (ETS) method. Despite being largely employed, especially for initializing more sophisticated and iterative optimization-based calibration techniques, ETS implementation is not straightforward, as the mapping between its estimated intermediate parameters and the sensor error parameters of interest (biases, scale factors, and misalignments) has not been clearly provided in the literature yet. In this article, hence, we carefully derive the latter, aiming at facilitating ETS numerical implementation. Withal, and also figuring as main contribution of this article, we provide analytical closed-form solutions for ETS, which are especially suitable for low-cost, real-time embedded applications. In order to validate their accuracy, insensitivity to local-minima convergence issues, and computational efficiency, we present simulations—including a Monte Carlo analysis—and hardware implementation, alongside a comprehensive comparison with state-of-the-art magnetometer calibration techniques.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Elliptic Localization With Imperfect Clock Synchronization for Known and
           Unknown Propagation Speed Scenarios

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      Authors: Yudong Xiao;Gang Wang;K. C. Ho;
      Pages: 1468 - 1481
      Abstract: In this article, we address the elliptic localization problem in the presence of clock synchronization errors at the receivers and transmitters, when the propagation speed is known as well as not known. For the known propagation speed scenario, we first show that the clock synchronization errors, when modeled as Gaussian random variables, can be treated as part of the composite noise in the measurement model without incurring performance loss in localization. Motivated by this result, we propose a generalized trust region subproblem solution for estimating the object position. For the unknown propagation speed scenario, we first formulate a nonconvex weighted least-squares problem. Such a nonconvex problem is solved by either one of the two proposed methods, semidefinite relaxation or grid search, to jointly estimate the object position and the propagation speed. Furthermore, we conduct the mean square error analysis to show that the proposed methods are able to reach the Cramer–Rao lower bound accuracy under Gaussian noise, which is validated by using simulated and semireal data.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Localization of Mixed Far-Field and Near-Field Incoherently Distributed
           Sources Using Two-Stage RARE Estimator

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      Authors: Ye Tian;Xinyu Gao;Wei Liu;Hua Chen;Gang Wang;Yunbai Qin;
      Pages: 1482 - 1494
      Abstract: In this article, a mixed source localization method utilizing a two-stage rank-reduction (RARE) estimator is investigated. Different from the existing methods, the proposed one is built on the incoherently distributed (ID) source model, which is more appropriate for multipath and fast time-varying channels. Firstly, a general array manifold (GAM) model is established, where nominal direction of arrivals (DOAs) and nominal ranges are extracted from the initial array manifold. By exploiting the shift invariance property of the far-field (FF) GAM and combining virtual source enumeration result, nominal FF DOA estimation is achieved by a 1-D RARE spectral search. Secondly, the oblique projection operation is adopted to separate near-field (NF) sources, and the nominal DOA and range parameters of NF sources are subsequently obtained by jointly utilizing the manifold separation technique and another two 1-D spectral searches. With the estimated nominal DOA and range parameters, the angular spread and range spread are then successfully estimated. Moreover, the Cramér–Rao bound for the considered case is also derived. Simulation results are presented to validate the effectiveness of the proposed method.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • High-Resolution Automotive Imaging Using MIMO Radar and Doppler Beam
           Sharpening

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      Authors: Scott L. Cassidy;Sukhjit Pooni;Mikhail Cherniakov;Edward G. Hoare;Marina S. Gashinova;
      Pages: 1495 - 1505
      Abstract: A highly detailed sensing of a vehicle's surrounding environment is a key requirement for the advancement of autonomous driving technology. While conventional automotive radar sensors remain robust under challenging weather conditions, poor cross-range resolution and high sidelobe levels present significant challenges. In this article, we propose an approach that combines multiple-input multiple-output (MIMO) beamforming with Doppler beam sharpening. We demonstrate a significant improvement in terms of cross-range resolution and, importantly, nearly 20-dB sidelobe suppression compared to conventional MIMO processing. This approach is investigated in detail and validated through theoretical analysis, simulation, and experiment using data recorded on a moving vehicle. We demonstrate performance that is comparable to a high-resolution mechanically scanned radar using a commercially available MIMO sensor.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Detection of Small Moving Targets in Cluttered Infrared Imagery

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      Authors: Adam Cuellar;Abhijit Mahalanobis;
      Pages: 1506 - 1517
      Abstract: Deep convolutional neural networks can achieve remarkable results for detecting and recognizing large- and medium-sized objects in visible band color images. However, the ability to detect small objects has yet to achieve the same level of performance. Our focus is on applications that require the accurate detection and localization of small moving objects that are distant from the sensor. State-of-the-art object detection and classification networks (such YOLOv3 and mask region-based CNN) are not well suited for finding small moving objects in infrared imagery, nor do they handle temporal information in video sequences. To overcome the limitations of these methods, we propose the moving target indicator network (MTINet), a new model specifically designed for detecting small moving targets in clutter. Several versions of the MTINet are presented with different refinements (such as spatial pyramid blocks and improved attention mechanism) to increase the probability of detection and reduce false alarm rates. The MTINet is trained to maximize the target to clutter ratio (TCR) metric, which represents the first use of the TCR loss function for detecting moving objects. To further challenge the MTINet, we also evaluated its performance with simulated sensor movement mimicking effects of image stabilization processes. Finally, we also propose a modification of the Reed-Xiaoli detector (originally developed for anomaly detection in hyperspectral data) to enable it to detect temporal anomalies caused by moving objects and refer to it as the temporal anomaly Reed-Xiaolis (t-ARX) algorithm. We find that the t-ARX algorithm can achieve better probability of detection at lower false alarm rates, while the MTINet is superior at finding difficult targets at higher false alarm rates. We then show that the combination of the two algorithms achieves the best overall performance.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Double-Opportunity Estimation via Altruism

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      Authors: Nitai Stein;Yaakov Oshman;
      Pages: 1518 - 1533
      Abstract: Based on the notion of altruism, we present an approach to cooperative parameter estimation in a system comprising two information-sharing agents. The underlying assumption is that the overall two-agent scheme can reach desired performance level even if only one of the agents performs satisfactorily, hence there exist two independent opportunities to estimate. The notion of altruism motivates a definition of cooperative estimation optimality that generalizes the common definition of minimum mean-squared error optimality. Fundamental equations are derived for two types of altruistic cooperative estimation problems, corresponding to heterarchical and hierarchical setups. Although these equations are, generally, hard to solve, their solution in the Gaussian case is straightforward and only entails the computation of the largest eigenvalue of the conditional covariance matrix and its corresponding eigenvector. Moreover, in the Gaussian case, the performance improvement of the two altruistic cooperative estimation techniques over the conventional (egoistic) estimation approach is shown to depend on the problem's dimensionality and statistical distribution. In particular, the performance improvement grows with the dispersion of the spectrum of the conditional covariance matrix, rendering the presented estimation approach especially appealing in ill-conditioned problems. The validity of the solution in the Gaussian case is illustrated numerically.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Attitude Coordination Control for Flexible Spacecraft Formation Flying
           With Guaranteed Performance Bounds

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      Authors: Yan Xiao;Anton de Ruiter;Dong Ye;Zhaowei Sun;
      Pages: 1534 - 1550
      Abstract: In this article, attitude coordination control for flexible spacecraft formation flying is investigated in the condition that common reference attitude is only available to a subset of the followers of the group. Measurement errors, immeasurable flexible modal variables, external disturbances, and model uncertainties of both rigid and flexible dynamics are addressed concurrently. Then, based on the sequential Lyapunov method, successively less conservative attitude coordination performance bounds can be obtained with the proposed distributed attitude coordination controller.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Joint Aperture and Transmit Resource Allocation Strategy for Multitarget
           Localization in the Phased Array Radar Network

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      Authors: Weiwei Zhang;Chenguang Shi;Jianjiang Zhou;Ruiguang Lv;
      Pages: 1551 - 1565
      Abstract: In practical application, the resources related to infrastructure and electromagnetic radiation are often limited for the phased array radar network (PARN). To more effectively exploit these limited resources, a joint aperture and transmit resource allocation (JATRA) strategy is built for the application of multitarget localization. The principle of the JATRA strategy is to minimize the total transmit power of the PARN by optimally allocating the aperture, power, and effective bandwidth under the constraints of the system resources, while achieving the predefined localization accuracy for each target. To begin with, the expressions of Cramér–Rao lower bound of target localization are derived for time of arrival (TOA), direction of arrival (DOA), as well as joint TOA and DOA, and adopted as localization metric. Subsequently, the JATRA strategy is constructed as a mixed-integer, nonlinear, and nonconvex optimization problem involving three adaptable vectors. In view of the characteristics presented in the construction model, a fast convergent two-step iterative optimization algorithm is designed to distribute three kinds of resources, together with its convergence and complexity well analyzed. Finally, the convergence of the two-step iterative algorithm is verified by simulation results, providing insights into underlying superiority of the JATRA strategy in comparison with other existing resource allocation schemes.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Improved DBF-MIMO-SAR Waveform Transmission Scheme for Reducing the Cost
           of DOF in the Elevation

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      Authors: Yu Wang;Daiyin Zhu;Guodong Jin;Shilin Niu;Xudong Wang;Yuan Cheng;Di Wu;
      Pages: 1566 - 1580
      Abstract: The echo separation solution based on digital beamforming (DBF) in the elevation is quite applicable to multiple-input multiple-output (MIMO) synthetic aperture radar (SAR). For the current DBF-MIMO-SAR schemes, however, at least ${2M-1}$ subapertures in the elevation must be employed to successfully separate the aliased signal returns induced by the $M$ simultaneously transmitted waveforms, which essentially increases the system complexity. To this end, this article proposes an improved waveform transmission scheme to exploit the potential benefits that the MIMO concept can provide for a practical remote sensing system with limited available channels. In this scheme, the basic signal segments are coded by the improved phase coding matrix, which is associated with the slow time. Afterward, time-shift weighting, using the decoding matrix, is implemented to remove the interference from close arrival angles. In this process, the interference segments in near or far range can also be canceled out. Consequently, the number of interferences has been halved, and thereby, compared with the already-proposed DBF-MIMO-SAR schemes, e.g., short-term shift-orthogonal, the designed scheme only needs ${M}$ elevation channels for the realization of DBF-MIMO-SAR. Finally. numerous simulations have been carried out to demonstrate that the proposed scheme shows great potential in terms of echo separation for channel-limited MIMO SAR systems.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Bistatic Radar Positioning of a Moving Target, Using Only Range and
           Range-Rate Measurements

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      Authors: Itzik Cohen;Nadav Levanon;
      Pages: 1581 - 1589
      Abstract: Of the many applications of bistatic (BS) radars, this article addresses the possibility to replace a monostatic radar with its highly directive antenna, with a coherent BS radar using a single short baseline between the transmitter and the receiver and no direction measurements. The method applies to a moving target and requires both range and range-rate BS measurements. Theory and field-test results demonstrate, on a two-dimensional scene, how several consecutive pairs of BS range $( r )$ and range-rate $( {dot{r}} )$ measurements of a moving target can provide the target's position, velocity, and heading (x, y, vx, vy). In a three-dimensional scene, with five estimated target parameters (x, y, h, vx, vy), a second receiver is needed, not in-line with the original baseline. The $( {r,dot{r}} )$ measurements distinguish the suggested concept from most other multistatic radars as well as the well-known multilateration positioning or interferometric angle-of-arrival estimation.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Adaptive Parameter Selection in the Simultaneous Transmission of CPM
           Communication and PN Ranging

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      Authors: Rui Xue;Tong Wang;
      Pages: 1590 - 1597
      Abstract: Ranging and communication are the two main functions of intersatellite link (ISL). The integration of these two functions and transmission of them on the same link can simplify the onboard equipment, reduce power consumption, save frequency resources, and integrate the ground station resources to reduce the complexity of the management system. In view of this, the regenerated pseudonoise (PN) ranging signal and continuous phase modulation (CPM) communication signal are combined at the phase level, and an integrated signal model of ranging communication based on CPM+PN is proposed in this article. To improve the accuracy of intersatellite ranging, an adaptive parameter selection algorithm is proposed in this article, which can adaptively select the ranging signal weighting factor according to the current channel state. The simulation results show that the adaptive parameter selection algorithm can greatly improve the ranging accuracy on the premise of ensuring the reliability of communication.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Robust Secure Transmission for Satellite Communications

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      Authors: Bin Jiang;Yingchun Yan;Li You;Jue Wang;Wenjin Wang;Xiqi Gao;
      Pages: 1598 - 1612
      Abstract: In recent years, satellite communications have become the focus of research on space–air–ground–sea integrated wireless communication networks because of their wide coverage. Due to the broadcasting nature of satellite communications, the security of satellite systems has become a critical issue. In this article, we study the secure transmission of satellite communications, focusing on the geostationary earth orbit (GEO) and low earth orbit (LEO) satellite scenarios, respectively. Because of the satellite's high mobility and long propagation delays, the transmitter side cannot obtain accurate channel state information (CSI). To this end, we establish the channel phase uncertainty model of GEO satellite users, the channel angle uncertainty model of LEO satellite users, and the norm-bounded model of eavesdroppers, respectively. Then, a corresponding robust secure transmission design is proposed. Since the resulting optimization problems are nonconvex and challenging to handle, we propose an algorithm that transforms the original problem into a series of convex optimization subproblems and obtains the beamforming weight vectors through iterative calculation. Simulation results indicate that the security and robustness performance of the proposed algorithms are significantly improved compared with the conventional baselines.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Unbiased Conversion of 3-D Bistatic Radar Measurements to Cartesian
           Position

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      Authors: Hagay Marom;Yaakov Bar-Shalom;Benny Milgrom;
      Pages: 1613 - 1623
      Abstract: Tracking with bistatic radar measurements is a challenging problem due to the nonlinear relationship between the radar measurements and the Cartesian coordinates, especially for long distances. This nonlinearity leads, for three-dimensional (3-D) bistatic radar, to a nonellipsoidal measurement uncertainty region in Cartesian coordinates, similar to a thin contact lens, that causes consistency problems for a tracking filter. A solution is proposed by developing an unbiased and statistically consistent conversion of the bistatic 3-D sine-space position measurements to Cartesian coordinates, based on second-order Taylor expansion. Such an approach was successfully used for monostatic radars but considered impractical for the bistatic case due to the difficulty to derive explicit conversion expressions, as done in this article. The recently developed 2-D approach for the bistatic case could not be successfully extended to 3-D and a different conversion was needed. It is shown that in contrast to the first-order conversion and the best nonlinear conversions (based on the cubature method), only the proposed conversion can cover the true uncertainty.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Event-Based Communication Strategies for Collaborative Inertial Radio SLAM

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      Authors: Joshua J. Morales;Joe J. Khalife;Zaher M. Kassas;
      Pages: 1624 - 1642
      Abstract: Event-based communication strategies for vehicles navigating by aiding their inertial navigation systems (INSs) with terrestrial signals of opportunity (SOPs) are developed. The following problem is considered. Multiple navigating vehicles with access to global navigation satellite system (GNSS) signals are aiding their on-board INSs with GNSS pseudoranges. While navigating, vehicle-mounted receivers draw pseudorange measurements from terrestrial SOPs with unknown emitter positions and unknown and unsynchronized clocks. The vehicles share INS data and SOP pseudoranges to collaboratively estimate the SOPs' states through an extended Kalman filter (EKF). After some time, GNSS signals become unavailable, at which point the navigating vehicles use shared INS and SOP information to continue navigating in a collaborative inertial radio simultaneous localization and mapping (CIRSLAM) framework. Two event-based communication strategies to share this information are developed, where instead of sharing information at a fixed-rate when measurements become available, information is only shared whenever any vehicle's position error could violate a user-specified position error threshold with some desired probability. Simulation results are presented demonstrating the tradeoff between localization performance and the accumulated transmitted data when the event-based transmission scheme is employed versus sharing data at the fixed-rate. Experimental results are presented demonstrating two unmanned aerial vehicles (UAVs) navigating in a CIRSLAM framework with SOP pseudoranges drawn from terrestrial cellular towers. The event-based communication scheme reduced the cumulative communicated data by 86.6% compared to a fixed-rate scheme, while maintaining the specified error constraint.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Optimal Sensor Placement for Hybrid Source Localization Using Fused
           TOA–RSS–AOA Measurements

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      Authors: Kuntal Panwar;Ghania Fatima;Prabhu Babu;
      Pages: 1643 - 1657
      Abstract: Source localization techniques incorporating hybrid measurements improve the reliability and accuracy of the location estimate. Given a set of hybrid sensors that can collect combined time of arrival, received signal strength, and angle of arrival measurements, the localization accuracy can be enhanced further by optimally designing the placements of the hybrid sensors. In this article, we present an optimal sensor placement methodology, which is based on the principle of majorization–minimization (MM), for the hybrid localization technique. We first derive the Cramer–Rao lower bound of the hybrid measurement model, and formulate the design problem using the A-optimal criterion. Next, we introduce an auxiliary variable to reformulate the design problem into an equivalent saddle-point problem, and then, construct simple surrogate functions (having closed form solutions) over both primal and dual variables. The application of MM in this article is distinct from the conventional MM (that is usually developed only over the primal variable), and we believe that the MM framework developed in this article can be employed to solve many optimization problems. The main advantage of our method over most of the existing state-of-the-art algorithms (which are mostly analytical in nature) is its ability to work for both uncorrelated and correlated noise in the measurements. We also discuss the extension of the proposed algorithm for the optimal placement designs based on D and E optimal criteria. Finally, the performance of the proposed method is studied under different noise conditions and different design parameters.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Distributed Task Scheduling for Multiple EOSs via a Game Theory Approach

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      Authors: Rui Feng;Zhiyun Lin;Peng Wu;Zhimin Han;Bo Wang;
      Pages: 1658 - 1669
      Abstract: In this study, we investigate the task scheduling problem for multiple earth observation satellites (EOSs) to achieve the maximal task observation ratio with the least repeated tasks. To begin, we build a task graph to describe feasible observation sequences for each EOS while satisfying its kinematic constraints. Next, we construct local utility functions for individual EOSs as metrics, and show that the task scheduling problem is indeed an exact potential game problem. Based on this finding, the collaborative goal for task scheduling is converted to the problem of solving for the Nash equilibrium (NE) of the game. Then, a sequential iterative algorithm and a simultaneous iterative algorithm are developed to solve for the NE in a distributed manner. Also, in the algorithms, a sieving scheme for EOSs is proposed to reduce the searching spaces. It is proved that our algorithms converge to the NE in finite steps and the global utility is shown to be monotonically increasing under certain conditions. Finally, the Bézier curve is used to smoothen the target observation path, based on which a model predictive control scheme is employed to design the control law of EOSs.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Parameter Estimation Using a Triad of Electrically Long Dipole Despite
           Data Model Mismatch

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      Authors: Wenye Zhong;Yang Song;Guofa Cai;
      Pages: 1670 - 1682
      Abstract: Most dipole-antenna signal processing algorithms have focused on “short dipole” whose physical length ($L$) is under ($1/10$) of a wavelength ($lambda$). Recent works now handle “long dipoles” of an electrical length $L/lambda in [0.1, 1]$. This article advances an algorithmic paradigm that uses short-dipole algorithm on long-dipole data. By studying the mismatched Cramér–Rao bound, we find that applying short-dipole algorithm to a long-dipole data model may yield parameters' estimates that are not far from their true values especially when $L/lambda$ is small. This phenomenon motivates a two-step algorithm where we apply short-dipole algorithm to get parameters' coarse estimates, which are then fine-tuned by an iterative algorithm. Our algorithm maximally retains the merits of the existing short-dipole algorithms while processing the signals received by a long dipole triad. Monte Carlo simulations verify the effectiveness of the proposed paradigm.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Concise Silicon Carbide DC Circuit Breaker Module for Satellite Electrical
           Systems

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      Authors: Chenzhen Wu;Yung C. Liang;
      Pages: 1683 - 1692
      Abstract: Fault protection and real-time monitoring of satellite electrical power systems are of importance for the advancement of modern satellite systems of high power, compact sizing, and long lifespan. Conventional protection methods could handle the overcurrent faults but lack flexibility in fault clearance time. With these important considerations, a compact and programable silicon carbide power MOSFET based dc circuit breaker module is developed to not only handle multiple levels of overcurrent faults with suitable time-delay protection scheme, but also provide the real-time monitoring of circuit breaker status by using the long range and Internet of Things technology. The proposed module has been implemented and its effectiveness was tested and confirmed in laboratory under various overcurrent fault conditions.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Online Frequency-Agile Strategy for Radar Detection Based on Constrained
           Combinatorial Nonstationary Bandit

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      Authors: Yuyuan Fang;Lei Zhang;Shaopeng Wei;Tao Wang;Jianxin Wu;
      Pages: 1693 - 1706
      Abstract: Frequency-agile (FA) transmission strategy plays a crucial role in radar antijamming applications. This strategy is usually designed or trained offline, which would lose the advantage of adaptability and flexibility when facing diverse jamming patterns and nonstationary target echoes. Considering the scenarios where a radar detects a target with strong nonstationary scattering characteristics under fast-variant interference, the radar is required to immediately adjust the FA transmission strategy to react to the variation of both jamming signals and target echoes quickly. In order to enhance radar transmission strategy in both generalization and flexibility aspects, an online FA strategy, called Combinatorial Discounted Thompson Sampling, is developed for the antijamming by exploiting the target's scattering change with the multiarmed bandit model. With the advantages of both optimal exploration and fast convergence, the proposed algorithm can efficiently adapt to the scattering fluctuation under dynamic frequency jamming emissions. Experimental comparisons with conventional deep reinforcement learning demonstrate the proposed algorithm's superiority for FA transmission strategy learning to boost radar detection performance under frequency response dynamics when avoiding frequency jamming.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • A Data-Driven Integrated Safety Risk Warning Model Based on Deep Learning
           for Civil Aircraft

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      Authors: Yuanyuan Guo;Youchao Sun;Yide He;Fangzhou Du;Siyu Su;Chong Peng;
      Pages: 1707 - 1719
      Abstract: With the extensive application of sensor technology, airlines accumulate a lot of flight data during fleet operations. Quick access recorder (QAR) is an important basis for aircraft state estimation and safety assessment, and it records the operating status of various aircraft systems. However, the current application of QAR is mainly reflected in the investigation and verification of accidents, but it fails to apply such continuous real-time data to safety monitoring, risk prediction, and early warning. Therefore, this article proposes a data-driven integrated safety risk warning model based on deep learning. Combined with the characteristics of QAR data and aircraft system failures, the failure mode and impact analysis, cause chain analysis, long short-term memory, and other methods are used to describe the development of risks caused by system failures and predict the trend of flight parameters of each system, and improve the ability to predict the risk and risk severity of the aviation system. Taking the aircraft refrigeration system as the case object, the safety risk warning model is validated to calculate the risk level may face and find out the hidden hazard sources of civil aircraft operation in advance, to improve the safety level of civil aircraft operation.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Smoothed Phase-Coded FMCW: Waveform Properties and Transceiver
           Architecture

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      Authors: Utku Kumbul;Nikita Petrov;Cicero S. Vaucher;Alexander Yarovoy;
      Pages: 1720 - 1737
      Abstract: Smoothed phase-coded frequency modulated continuous waveform (SPC-FMCW), which is aimed to improve the coexistence of multiple radars operating within the same frequency bandwidth, is studied, and the receiving strategy with a low analog-to-digital converter sampling requirement is investigated. The Gaussian filter is applied to obtain smooth waveform phase transitions, and then, quadratic phase lag compensation is performed before waveform transmission to enhance decoding. The proposed waveform is examined in different domains, and its waveform properties are analyzed theoretically and demonstrated experimentally. Both simulation and experimental results show that the introduced waveform with the investigated processing steps helps combine all advantages of the FMCW waveform, including hardware simplicity and small operational bandwidth of the receiver, with the advantages of phase coding.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • NN-Based Fixed-Time Attitude Tracking Control for Multiple Unmanned Aerial
           Vehicles With Nonlinear Faults

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      Authors: Xiaohong Zheng;Hongyi Li;Choon Ki Ahn;Deyin Yao;
      Pages: 1738 - 1748
      Abstract: This article focuses on the fixed-time fault-tolerant attitude tracking control problem for multiple unmanned aerial vehicles (MUAVs) with nonaffine nonlinear faults. First, the command filter and neural networks (NNs) are employed to characterize unknown nonlinearities in MUAVs, and the update law of NN is developed via convex optimization technique. Second, the algebraic loop problem caused by nonaffine nonlinear faults is adequately solved by introducing the Butterworth low-pass filter. Then, the curve-fitting method is utilized to construct a piecewise virtual control signal to avoid the singularity problem in fixed-time control. Furthermore, based on the Lyapunov stability theory, a general fixed-time stability criterion is adopted to prove that the designed fault-tolerant attitude controller can guarantee the stability of MUAVs in fixed time. Finally, the effectiveness of the proposed control design method is verified via illustrative examples.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Modeling of Number of Sources Detection Under Nonideal Conditions Based on
           Fuzzy Information Granulation

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      Authors: Rui Zhang;Kaijie Xu;Shengqi Zhu;Mengdao Xing;Yinghui Quan;
      Pages: 1749 - 1757
      Abstract: In this article, we exploit a granular-based modeling scheme to realize the number of sources detection under nonideal conditions (in low signal-to-noise ratio levels and small snapshots scenarios), in which the idea of information granules and granular computing is integrated with the fuzzy set theory. In the developed scheme, a collection of eigenvalues, which is calculated by the array output correlation matrix, is constructed as a time series. Then, the principle of justifiable granularity criterion is introduced to split the time series into two regions so as to establish a set of upper and lower bounds of prototypes for the signal and noise subspaces. Subsequently, the fuzzy C-means-based encoding and decoding mechanism is employed to optimize the prototypes. During this process, the encoding mechanism is used to produce a pair of information granules, and the decoding mechanism is used to evaluate the quality of information granules. After several rounds of iteration, an optimized prototype vector and a partition matrix are generated. Finally, the structure of the time series is exposed (encoded into) by an optimized prototype vector and a partition matrix, and the number of sources can be determined conveniently through the partition matrix. Simulation results show that the proposed method outperforms the commonly used methods under nonideal conditions.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Extended Double-Delta Correlator Technique for GNSS Multipath Mitigation

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      Authors: Yudong Sun;Zheng Yao;Mingquan Lu;
      Pages: 1758 - 1773
      Abstract: Multipath is one of the main error sources in the global navigation satellite system (GNSS). Many multipath mitigation methods have been proposed, such as the narrow correlator technique and the double-delta (DD) correlator technique. In light of the binary phase shift keying (BPSK) modulated signals used in many GNSS, an extended DD (EDD) correlator technique expanding from the DD correlator, which uses multiple pairs of correlators with more general spacing and weight, is proposed in this article. Furthermore, the article provides the discriminator structure, the closed-form expressions for multipath error envelope under infinite bandwidth, and the closed-form expressions for the relationship between multipath error, thermal noise performance, and design parameters of the discriminator. Based on the explicit performance expressions, the appropriate selection principles of parameters are given and verified by theoretical analysis and simulation. The results show that the proposed method can improve the performance optimization freedom of the DD technique without significantly increasing the design complexity. Moreover, the multipath performance is better than DD under infinite bandwidth and has great adaptability to limited bandwidth and the next-generation GNSS signals, such as binary offset carrier (BOC) and multiplexed BOC (MBOC). The EDD technique can also be utilized as a noncoherent discriminator and has better antimultipath performance. Furthermore, the EDD technique can achieve a balance between multipath mitigation performance and thermal noise performance by adjusting correlator spacing and weight and can be self-adaptive to multipath relative amplitude in the environment.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • $H_{infty}$ +Filtering+for+Nonlinear+Stochastic+Systems+With+Multiplicative+Noises+via+Carleman+Linearization+Technique&rft.title=IEEE+Transactions+on+Aerospace+and+Electronic+Systems&rft.issn=0018-9251&rft.date=2023&rft.volume=59&rft.spage=1774&rft.epage=1786&rft.aulast=Zhou;&rft.aufirst=Li&rft.au=Li+Sheng;Yuechao+Wang;Ming+Gao;Yichun+Niu;Donghua+Zhou;">Finite-Time $H_{infty}$ Filtering for Nonlinear Stochastic Systems With
           Multiplicative Noises via Carleman Linearization Technique

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      Authors: Li Sheng;Yuechao Wang;Ming Gao;Yichun Niu;Donghua Zhou;
      Pages: 1774 - 1786
      Abstract: In this article, the problem of finite-time $H_infty$ filtering is dealt with for general nonlinear stochastic systems with multiplicative noises. The nonlinear system under investigation is not only disturbed by state-dependent noises, but also corrupted by external disturbance. By utilizing the Carleman linearization technique, a linear parameter-varying system related to state estimation is obtained and a polynomial nonlinear filter is constructed for nonlinear stochastic systems. Then, a sufficient condition in terms of parameter-dependent linear matrix inequalities (PDLMIs) is established to guarantee the finite-time boundedness and certain $H_infty$ performance of the filtering error dynamics. Moreover, the parameters of the polynomial nonlinear filter are derived by solving PDLMIs via the sum of squares decomposition approach. Finally, the effectiveness of the developed filtering scheme is demonstrated by two examples, with one concerning the rotary steerable drilling tool system.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Efficient Preprocessing of Site-Specific Radio Channels for Virtual Drive
           Testing in Hardware Emulators

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      Authors: Allan Wainaina Mbugua;Yun Chen;Leszek Raschkowski;Yilin Ji;Mohamed Gharba;Wei Fan;
      Pages: 1787 - 1799
      Abstract: Performance testing under realistic propagation channel conditions is essential for virtual drive testing, where radio channel emulators are typically employed in the laboratory for such applications. Optimal allocation of tap resources in the channel emulator is critical in hardware-in-the-loop emulation of radio channels due to the constraint of real-time operation requirements, hardware complexity, and cost. As a result, replaying arbitrary site-specific, e.g., measured or ray tracing (RT) simulated radio channels in channel emulators requires delay alignment and reduction of the number of multipath components in the channel to match the available hardware resources. However, such operations would essentially introduce inaccuracies in the emulated channel. In this article, a framework for preprocessing site-specific radio channels for hardware emulation is proposed. The delay alignment problem is formulated as a finite impulse response filter design problem, whereas the subsequent tap reduction and selection process is formulated as a sparse approximation problem. This approach enables maximization of the accuracy of the reproduced channel frequency response and Doppler profile in the hardware emulator using a limited number of taps. The efficiency of the proposed framework is demonstrated experimentally with a dynamic vehicular RT simulated channel, which is replayed on a state-of-the-art radio channel emulator.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Large Region Targets Observation Scheduling by Multiple Satellites Using
           Resampling Particle Swarm Optimization

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      Authors: Yi Gu;Chao Han;Yuhan Chen;Shenggang Liu;Xinwei Wang;
      Pages: 1800 - 1815
      Abstract: The last decades have witnessed a rapid increase of Earth observation satellites (EOSs), leading to the increasing complexity of EOSs scheduling. On account of the widespread applications of large region observation, this article aims to address the EOSs observation scheduling problem for large region targets. A rapid coverage calculation method employing a projection reference plane and a polygon clipping technique is first developed. We then formulate a nonlinear integer programming model for the scheduling problem, where the objective function is calculated based on the developed coverage calculation method. A greedy initialization-based resampling particle swarm optimization (GI-RPSO) algorithm is proposed to solve the model. The adopted greedy initialization strategy and particle resampling method contribute to generating efficient and effective solutions during the evolution process. In the end, extensive experiments are conducted to illustrate the effectiveness and reliability of the proposed method. Compared to the traditional PSO and the widely used greedy algorithm, the proposed GI-RPSO can improve the scheduling result by 5.42% and 15.86%, respectively.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Cognitive Sparse Beamformer Design in Dynamic Environment via Regularized
           Switching Network

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      Authors: Xiangrong Wang;Weitong Zhai;Maria Sabrina Greco;Fulvio Gini;
      Pages: 1816 - 1833
      Abstract: Beamformers employ an array of antenna elements to collect the electromagnetic wave in the spatial domain and filter the corrupted signal in the element-space or beam-space. The spatial filtering performance of both element-space and beam-space beamformers is jointly determined by two key factors, i.e., beamformer geometry and excitation weights. In this work, we propose a cognitive sparse beamformer, which is capable of swiftly adapting entwined beamformer geometry and excitation weights according to the environmental dynamics through a “perception–action” cycle. In the “perception” step, situational information is extracted from the collected real-time data, and the sparse beamformer is updated in the “action” step via a regularized switching network, which divides the large array into groups and one antenna or beam is replaced with other candidates in the same group in the metric of array gain (AG) during each iteration. To circumvent the prohibitive computations resulted from matrix inversion accompanying with each update, closed-form formulas are derived to quantify the AG variation, thus facilitating efficient online beamformer reconfiguration. Extensive simulations show the effectiveness of the proposed cognitive sparse beamformer design method.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Recursive Algorithms for the Estimation of Multiple Superimposed Undamped
           Tones and Their Application to Radar Systems

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      Authors: Pasquale Di Viesti;Alessandro Davoli;Giorgio Guerzoni;Giorgio M. Vitetta;
      Pages: 1834 - 1853
      Abstract: In this article, two recursive algorithms for the detection of multiple superimposed tones in noise and the estimation of their parameters are derived. They are based on a maximum likelihood approach and combine an innovative single-tone estimator with a serial cancellation procedure. Our numerical results lead to the conclusion that the developed methods can achieve a substantially better accuracy–complexity tradeoff than various related techniques in the presence of multiple closely spaced tones. Moreover, they can be exploited to detect multiple closely spaced targets and estimate their spatial coordinates in multiple-input multiple-output frequency-modulated continuous wave radar systems.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Asynchronous Nonuniform Distributed Multitarget Tracking Filter Based on
           Asymmetric Alpha-Divergence Consensus

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      Authors: Yuqin Zhou;Liping Yan;Hui Li;Yuanqing Xia;
      Pages: 1854 - 1866
      Abstract: With more and more extensive applications of target tracking, distributed multitarget tracking (DMT) becomes an important research direction. However, the synchronization characteristics of some sensor networks cannot be effectively guaranteed due to communication delay, nonuniform sampling, etc. Therefore, a DMT algorithm for asynchronous nonuniform multisensor networks (AN-WSN) is studied in this article. First, a CD-CPHD algorithm with the multistep birth process and time-triggered structure (TCD-CPHD) is proposed by using the continuous-discrete multitarget dynamic (CD) model and the cardinalized probability hypothesis density (CPHD); second, a TCD-CPHD trigger structure based on asymmetric alpha-divergence (AAD) is designed to reduce the communication rate of TCD-CPHD by adaptively calculating the time-trigger index; third, the fusion rule of AAD consensus is derived to construct the fusion process of the proposed DMT algorithm; finally, by combining the above structures and the fusion rule, the implementation processes of the proposed DMT algorithm are given. Theoretical analysis and exhaustive experimental analysis show the effectiveness of the proposed algorithm.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Distributed Formation Centroid Tracking Control of Clustered Rotorcraft

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      Authors: Yongbin Sun;Yao Zou;Xiuyu He;Qiang Fu;Jiang Wu;
      Pages: 1867 - 1878
      Abstract: We design a distributed control algorithm for clustered rotorcraft to cooperatively realize the formation centroid tracking objective in this article. In particular, the rotorcraft cluster are capable of constructing a prescribed configuration while making the configuration centroid track a reference trajectory. However, constrained by decentralization, each rotorcraft has no idea where the configuration centroid is. Besides, the reference trajectory information is just available to parts of rotorcraft. To begin with, resorting to the cascaded system stability theory, the original formation centroid tracking problem of clustered rotorcraft is translated into designing a bounded transition force and an applied torque for the respective stabilization of the nominal position error dynamics and attitude error dynamics of each individual. Then, by introducing two feasible distributed observers to accurately estimate the configuration centroid and reference acceleration, respectively, a transition force with saturation attribute is designed such that the nominal position error dynamics is stabilized. With such a saturated transition force, a choice criterion of control parameters that is independent of system states is built for the nonsingular demand attitude extraction. Next, an applied torque is designed such that the attitude error dynamics is stabilized. A detailed stability analysis using the generalized Lyapunov theory is carried out. Simulation results verify the effectiveness of the designed distributed control algorithm.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • MarsSim: A High-Fidelity Physical and Visual Simulation for Mars Rovers

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      Authors: Ruyi Zhou;Wenhao Feng;Liang Ding;Huaiguang Yang;Haibo Gao;Guangjun Liu;Zongquan Deng;
      Pages: 1879 - 1892
      Abstract: Simulation has deeply infiltrated into the development and validation of planetary rover technologies concerning mobility and autonomy, by providing large amounts of data in a variety of conditions and environments, as well as high-fidelity prototypes. Prevalent approaches for rover simulation focus either on physical behaviors or visual scenarios. In this article, we present a simulator named MarsSim developed upon Robotic Operating System/Gazebo platform that supports both physical and visual realistic simulations. The interaction between the wheel and the rough deformable terrain is modeled with improved contact solutions, and the model is integrated into a refined physical simulation architecture as an independent terramechanics plugin. Using multiscale planetary data and representation models, Martian scenarios are constructed, considering characteristics in terms of the surface, rock, and atmosphere. Compared with experiments, the terramechanics plugin shows great modeling accuracy in fitting interactive force/torque and slip-sinkage phenomenon. The simulation of traverses with a six-wheeled planetary rover on Martian landscape is demonstrated with near-photoreal images, coupled with physical-realistic locomotive data under different terrains.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Multistage Least Squares Algorithms for Clutter Suppression in Airborne
           Passive Radar Based on Subband Operation

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      Authors: Jinxin Sui;Jun Wang;Luo Zuo;Jie Gao;
      Pages: 1893 - 1909
      Abstract: This article, first, analyzes the influence of utilizing the space-time adaptive processing approaches in airborne passive radar (APR) systems on the dimension of the clutter subspace, and the signal-plus-noise ratio loss of the target, and illustrates that it is necessary to propose clutter cancellation algorithms suitable for APR systems. Combined with the property of APR systems, the multistage least squares algorithm based on subband operation (MLS-S) and the MLS algorithm based on subband operation in temporal domain (MLS-ST) are proposed for the Doppler-shift clutter cancellation. The first method, in the case of the clutter with integer Doppler-shift bins, proves to be a simple solution. The second approach, at the expense of an additional stage, is suitable for more situations. Due to the use of Doppler-angle-dependence and subband operation to coarsen the range resolution, the proposed methods not only suppress effectively clutter along the clutter ridge, but also cancel the fractional-order-range clutter. In addition, the computational complexity of the proposed algorithms is low, and the clutter cancellation operations can be performed in parallel, which provide the possibility of real-time clutter suppression for APR systems. The feasibility of the proposed approaches is verified by diverse simulated scenarios.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • SAR-PeGA: A Generation Method of Adversarial Examples for SAR Image Target
           Recognition Network

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      Authors: Weijie Xia;Zhe Liu;Yi Li;
      Pages: 1910 - 1920
      Abstract: Deep learning (DL) is widely used in automatic target recognition (ATR) of synthetic aperture radar (SAR) images. Related researches show that DL models for SAR ATR are vulnerable to adversarial examples attack in the digital domain. However, how to generate adversarial examples in practical scenarios is critical and challenging. In this article, we propose a systematic SAR perturbation generation algorithm for target recognition network. First, assuming that some reflection phase tuning samples are located in the fixed area of SAR target, we adjust the phase characteristics of reflected signal with variable phase sequences. Second, we take the imperceptible perturbations from universal adversarial perturbations as reference. Then, we construct the unconstrained minimum optimization model to find the specific phase sequences of tuning samples and optimize the model with the adaptive moment estimation optimizer. Finally, SAR adversarial examples can be flexibly generated through the proposed deceptive jamming model. Experimental results demonstrate that the proposed method can generate imperceptible jamming and effectively attack three classical recognition models.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • PSO-Based Time Optimal Rapid Orientation for Micronano Space Robot

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      Authors: Yuchen Liu;Zhonghe Jin;Lai Teng;
      Pages: 1921 - 1934
      Abstract: Simultaneous multidirectional orientation tasks on space robots exhibit strong dynamic coupling between the manipulators and the base-spacecraft, and this phenomenon is more obvious in the micronano space robot. Regarding to the highly coupled dynamic system of micronano space robot and its nonholonomic constraints, a multidirectional rapid orientation method of micronano space robot based on optimization theory is proposed in this article. Dynamic model of satellite-manipulators cooperative operation micronano space robot is established by the combination of virtual manipulator and Newton–Euler method. Then, taking the acceleration continuous cubic polynomial trajectory planning method and the dynamics-based feedback linearization controller as an example, the particle swarm optimization method is used to solve the time and path nodes of the orientation process of the micronano space robot. Finally, three typical spatial orientation problems are simulated to verify the feasibility and rapidity of this orientation method: 1) simultaneous orientation; 2) assisted orientation; and 3) cooperative braking. Furthermore, the article presents the structure of the objective function for optimization in different multicomponent and multiobjective coorientation tasks.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Efficient Gaussian Mixture Modeling of Long-Range 2-D Radar Measurements

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      Authors: Benjamin P. Davis;W. Dale Blair;
      Pages: 1935 - 1945
      Abstract: In some practical radar systems of interest, the standard EKF linearization approach applied to a nonlinear measurement transformation is ineffective. In particular, if measurements are performed in polar coordinates and the crossrange error is much greater than the range error, then the true error region in Cartesian space is no longer well approximated by a Gaussian distribution. This effect is known as the “contact lens” problem, and various approaches have been proposed to alleviate it, including particle and Gaussian mixture (GM) filters. In this work, a method is presented for modeling Cartesian converted measurement distributions, which suffer from the contact lens effect using Maximum Likelihood (ML) GM parameters. In order to allow an efficient implementation of this process in a GM Kalman filter, a normalization of the ML parameters is introduced so that parameters can be computed offline and efficiently stored in a lookup table. Simulation results are presented to illustrate the method and confirm the results.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • A Fractional-Order Method for Metalearning About Aerospace Target
           Classification

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      Authors: ZhongLiang Yu;Jianfeng Lv;
      Pages: 1946 - 1954
      Abstract: Meta-learning can sum up the experience from the learned tasks, and solve the problems of datasets scarce or expensive and insufficient model generalization ability, which is the inadequate of traditional machine learning. Metalearning can obtain a well initial model, which can quickly generalize after a few adjustments to solve new tasks with good performance. However, model-agnostic metalearning (MAML) faces the problem of convergence difficulties, and easily prone to concussion late in training. We employ fractional order to MAML, which can retain past task gradient for a better stabilized and generalized model. We proposed a method based on fractional order and MAML (FracMAML), which can apply to a method based on metalearning, such as MAML and Reptile. Our proposed method can obtain a better initial model via fractional order. We take advantage of metalearning on few-shot problems to solve the aerospace targets classification problem, and proposed an Aerospace dataset. We employed FracMAML on MiniImagenet and Omniglot, which obtain state-of-the-art accuracy than some classical metalearning methods, such as MAML, Reptile, and so on. Finally, we verify the FracMAML method on aerospace targets classification task based on our Aerospace dataset, which performed well; further, verify the versatility of our algorithm.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Robust Adaptive Control of Hypersonic Flight Vehicle With
           Aero-Servo-Elastic Effect

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      Authors: Xia Wang;Bin Xu;
      Pages: 1955 - 1964
      Abstract: This article investigates the notch filter based robust adaptive control for the longitudinal dynamics of flexible hypersonic flight vehicle using finite-time design and online estimation. Considering the aero-servo-elastic effect caused by the elastic vibration at sensor position, the recursive least-square algorithm is employed to track the natural frequencies of the flexible modes, which can then be used as the center frequencies for the cascade-type notch filter. Based on the filtered signal, the robust adaptive control is studied where the neural network is used to handle aerodynamics uncertainty and the disturbance observer is employed to compensate flexible coupling. The prediction error is constructed for the update laws while the nonlinear function is further developed to achieve the finite-time tracking. The uniformly ultimately bounded stability is guaranteed under the proposed approach. The effectiveness of the design is illustrated through the simulation study.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Nonlinear Disturbance Observer Based Adaptive Explicit Nonlinear Model
           Predictive Control Design for a Class of Nonlinear MIMO System

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      Authors: Lakshmi Dutta;Dushmanta Kumar Das;
      Pages: 1965 - 1979
      Abstract: In this article, a nonlinear disturbance observer (NDO)-based adaptive explicit nonlinear model predictive control scheme is proposed to compensate for external disturbance and parametric uncertainty for a class of nonlinear multi-input-multi-output (MIMO) systems. Here, the analytical solution of the proposed adaptive control scheme is developed by approximating the tracking errors and control efforts with the Taylor series expansion method. In this approach, a NDO is used to observe the unknown external disturbance of the system. To restrict the parameters from leaving the compact parameter space, an adaptive parameter estimator using projection-based parameter adaptation laws is used. The performance of the designed control technique is enhanced by incorporating the estimated disturbance and estimated system parameters in the updating control law. Using an aerodynamic laboratory set-up known as the twin-rotor MIMO system, the effectiveness of the proposed control algorithm has been verified. Simulation and real-time results show that the proposed control algorithm performs better than the existing control algorithm in the presence of unknown external disturbances and parameter uncertainties.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Investigation of the Retrieval Dynamics of the Tethered Satellites Using
           ANCF-ALE Variable-Length Element

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      Authors: Zhengfeng Bai;Xin Jiang;Xuyun Fu;
      Pages: 1980 - 1988
      Abstract: Tether satellite system (TSS) comprises two satellites connected by a flexible tether and has wide applications, such as orbital transferring, deep space exploration, and so on. In this article, a variable-length element, based on the absolute nodal coordinate formulation (ANCF) in the framework of arbitrary Lagrangian–Eulerian (ALE) description, is used to predict the characteristics of length variation and flexibility of the tether in the phases of retrieval and station-keeping. Then, to achieve a stable retrieval implementation and take the underactuation property of the TSS into account, an optimal retrieval trajectory is programmed using the Gauss pseudospectral method-based dynamic optimization. Three different retrieval schemes are implemented using the developed ANCF-ALE model. Numerical studies show that, compared with the dumbbell model, the ANCF-ALE-based model can predict the tension of the tether in the phase of retrieval. Results indicate that the tether tension is sensitive to the ratio of change of the tether retrieval velocity. Improper retrieval scheme may induce the intensive oscillation in the tether tension, or a switched state of the tether between pseudoslack and tensile. In the optimization for optima trajectory programming, weight of ratio of tether velocity in the objective function should be considered carefully to realize a robust retrieval implementation.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Satellite Observation and Data-Transmission Scheduling Using Imitation
           Learning Based on Mixed Integer Linear Programming

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      Authors: Qingyu Qu;Kexin Liu;Xijun Li;Yunfan Zhou;Jinhu Lü;
      Pages: 1989 - 2001
      Abstract: The Earth observation satellites (EOSs) scheduling problem is generally considered as a complex combinatorial optimization problem due to various technical constraints. It is significant to develop efficient computational frameworks to solve this problem. In this article, an intelligent EOSs scheduling framework is developed using imitation learning based on mixed integer linear programming (MILP). The scheduling framework is composed of two processes: preprocessing, modeling, and solving process. In the preprocessing process, an analytical method to generate the available time windows of an EOS is derived after considering the effects of Earth's $J_{2}$ perturbation on the elliptic orbit. Based on the preprocessing results, this problem is formulated as an MILP model in the modeling process. In the solving process, a smart algorithm is proposed based on imitation learning for branch-and-bound to accelerate the solving process. Compared with normal imitation learning, a data selection method works in our algorithm to avoid potential misleading for learning. Besides, an iterative view is also adopted to improve the performance of the trained strategy. In the end, several real-world EOSs scheduling scenarios are investigated to demonstrate the reliability and high efficiency of this framework.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Quantum Computing for Applications in Data Fusion

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      Authors: Veit Stooβ;Martin Ulmke;Felix Govaers;
      Pages: 2002 - 2012
      Abstract: Quantum computing promises significant improvements of computation capabilities in various fields, such as machine learning and complex optimization problems. Rapid technological advancements suggest that adiabatic and gate base quantum computing may see practical applications in the near future. In this work, we adopt quantum computing paradigms to develop solvers for two well-known combinatorial optimization problems in information fusion and resource management: 1) multitarget data association and weapon target assignment. These problems are NP-hard (non)linear integer programming optimization tasks, which become computationally expensive for large problem sizes. We derive the problem formulations adapted for the use in quantum algorithms and present solvers based on adiabatic quantum computing and the quantum approximative optimization algorithm. The feasibility of the models is demonstrated by numerical simulation and first experiments on quantum hardware.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Ambiguity Function Based High-Order Translational Motion Compensation

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      Authors: Zhenyu Zhuo;Lan Du;Xiaofei Lu;Ke Ren;Lu Li;
      Pages: 2013 - 2019
      Abstract: Micro-Doppler feature plays an important role in cone-shaped target recognition and parameter estimation. However, translational motion causes shifting, tilting, and aliasing in micro-Doppler spectrum and influences the extraction of micro-Doppler features. Most existing methods do not consider higher order translation compensation. In this article, a high-order translational motion compensation method is proposed. First, the high-order ambiguity function (HAF) of a periodical polynomial phase signal exhibits periodicity along the lag axis and reaches the peak concentration when the lag is equal to the micromotion period. The micromotion period can be obtained by searching the peak concentration of echo's HAF. Then, the translational jerk and acceleration are, respectively, compensated by searching the peaks of the second- and third-order HAFs. Last, convolution is operated on the frequency spectrum to find the symmetric center located at the Doppler shift frequency, and the residual translational velocity can be estimated. Experimental results based on electromagnetic computation data show that the proposed method can accurately achieve high-order translational compensation.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • On Performance of IRS-Assisted Hybrid Satellite–Terrestrial
           Cooperative Communication

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      Authors: Kshitija Dolas;M. R. Bhatnagar;
      Pages: 2020 - 2028
      Abstract: In this paper, an intelligent reflecting surface (IRS)-assisted hybrid satellite–terrestrial cooperative system is considered, where direct transmission between the satellite and the destination is not present due to the masking effect and the destination node receives amplify-and-forward relayed transmission through an IRS. It is assumed that the channel between satellite and relay undergoes shadowed Rician fading, while the cascaded relay–IRS–destination link follow Rayleigh distribution. The performance of the considered system is evaluated by deriving an approximate closed-form expression for the average symbol error rate (SER) of the considered system for $M$-ary phase-shift keying modulation. Further, analysis for diversity order is also carried out using the asymptotic SER. In addition to this, analytical expressions for upper bound on the ergodic capacity and the outage probability of the considered system are also obtained.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Log-Linear Error State Model Derivation Without Approximation for INS

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      Authors: Lubin Chang;Yarong Luo;
      Pages: 2029 - 2035
      Abstract: Through assembling the navigation parameters as the matrix Lie group state, the corresponding inertial navigation system (INS) kinematic model possesses a group-affine property. The Lie logarithm of the navigation state estimation error satisfies a log-linear autonomous differential equation. These log-linear models are still applicable even with arbitrarily large initial errors, which are very attractive for INS initial alignment. However, in existing works, the log-linear models are all derived based on first-order linearization approximation, which seemingly goes against their successful applications in INS initial alignment with large misalignments. In this work, it is shown that the log-linear models can also be derived without any approximation; the error dynamics for both left- and right-invariant errors in continuous time are given in the matrix Lie group $mathrm{S}{mathrm{E}}_2( 3 )$ for the first time. This work provides another evidence for the validity of the log-linear model in situations with arbitrarily large initial errors.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Direct Position Determination Using Compressive Sensing Measurements
           Without Reconstruction

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      Authors: Ming-Yi You;An-Nan Lu;Yun-Xia Ye;Kai Huang;Caiyi Lou;
      Pages: 2036 - 2043
      Abstract: This article proposes a direct position determination (DPD) method for stationary emitters with compressed signal measurements. Employing Hadamard matrix properties, the method estimates the source location directly in the compressing measurement domain, without the step of signal reconstruction and time-differences-of-arrival parameter extraction. In the case of free-space propagation, an augmented DPD method is proposed to further utilize the position-related received signal strength information. In addition, the Cramér–Rao lower bounds for the emitter position of both DPD methods are derived for performance evaluation.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • An Anomaly Detection Method for Satellites Using Monte Carlo Dropout

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      Authors: Mohammad Amin Maleki Sadr;Yeying Zhu;Peng Hu;
      Pages: 2044 - 2052
      Abstract: Recently, there has been a significant amount of interest in satellite telemetry anomaly detection (AD) using neural networks (NN). For AD purposes, the current approaches focus on either forecasting or reconstruction of the time series, and they cannot measure the level of reliability or the probability of correct detection. Although the Bayesian neural network (BNN)-based approaches are well known for time series uncertainty estimation, they are computationally intractable. In this article, we present a tractable approximation for BNN based on the Monte Carlo (MC) dropout method for capturing the uncertainty in the satellite telemetry time series, without sacrificing accuracy. For time series forecasting, we employ an NN, which consists of several long short-term memory (LSTM) layers followed by various dense layers. We employ the MC dropout inside each LSTM layer and before the dense layers for uncertainty estimation. With the proposed uncertainty region and by utilizing a postprocessing filter, we can effectively capture the anomaly points. Numerical results show that our proposed time series AD approach outperforms the existing methods from both prediction accuracy and AD perspectives.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • A Robust Variability Index CFAR Detector for Weibull Background

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      Authors: Xinyang Wang;Yang Li;Ning Zhang;
      Pages: 2053 - 2064
      Abstract: The Weibull distribution is commonly used for clutter modeling as it can provide a good fit to the experimental data over a wide range of conditions, and as such there is considerable attention to the development of constant false alarm rate (CFAR) detectors under such a clutter model assumption. The detection backgrounds of some radar systems are nonhomogeneous, which is a challenging task for CFAR detection. The variability index CFAR (VI-CFAR) detector is proposed for the nonhomogeneous Gaussian clutter in the literature. However, it might increase the false alarm rate significantly in the Weibull clutter due to the target-like clutter samples, and its performance degrades in the nonhomogeneous clutter with the presence of interfering targets at both sides of the cell under test. To address these problems, we propose a robust variability index CFAR detector for the Weibull background (RWVI-CFAR) with known shape parameters in this article. In the RWVI-CFAR, we extend the VI-CFAR to the Weibull clutter and design an automatic outlier censoring maximum likelihood CFAR (AOCML-CFAR) strategy to improve the detection performance in multiple-target situations. The proposed AOCML-CFAR strategy exploits the sparsity of interfering targets to censor the outliers adaptively. By selecting the AOCML-CFAR strategy, the anti-interference capability of the RWVI-CFAR is significantly improved. Simulated and experimental results show the favorable and robust performance of the RWVI-CFAR in the Weibull background.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Solar Sail Augmented Hohmann Transfer

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      Authors: Alessandro A. Quarta;Giovanni Mengali;Lorenzo Niccolai;Christian Bianchi;
      Pages: 2065 - 2071
      Abstract: The aim of this correspondence is to analyze the performance of a solar sail-based spacecraft in a two-impulse orbit transfer between circular and coplanar heliocentric orbits of assigned radii. In particular, assuming a transfer trajectory with a sweep angle and a flight time equal to those of a classical Hohmann orbit, the sail propulsive acceleration is used to minimize the total velocity variation required by the two tangential impulses. In this sense, the article quantifies the optimal performance of a solar sail augmented Hohmann transfer as a function of the sail characteristics.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • Pseudosymmetric Enclosed Layout Transistors for Radiation Hardened Analog
           Applications

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      Authors: Gustavo Paz Platcheck;Guilherme Schwanke Cardoso;Tiago Roberto Balen;
      Pages: 2072 - 2076
      Abstract: The enclosed layout transistor is an alternative to reduce the radiation sensitivity of CMOS devices by avoiding thick field oxide paths between source and drain terminals. This prevents the increase of leakage current of devices working under radiation. The commonly adopted square geometry of this design brings asymmetry between source and drain, modifying characteristics such as output conductance and capacitance, if compared to a traditional layout. Therefore, considering analog designs, this may complicate the process of mapping a nonhardened design onto a radiation tolerant version, even if the aspect ratios ($W/L$) of the transistors are designed to be the same. In this article, we propose a pseudosymmetric version of enclosed layout devices in order to better approximate its electrical characteristics to the conventional layout style. This way, no significant modification on simulation and design validation flow is necessary. The devices were fabricated in a 130 nm process, being then characterized and compared with regular (nonsymmetric) ELTs as well as to conventional (two-edge) layout transistors. Results show a good agreement between the tested parameters of the pseudosymmetric ELTs and the correspondent two-edge devices.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • 2D-DOD and 2D-DOA Estimation Using Sparse L-Shaped EMVS-MIMO Radar

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      Authors: Fangqing Wen;Junpeng Shi;Jin He;Trieu-Kien Truong;
      Pages: 2077 - 2084
      Abstract: It is well known that electromagnetic vector sensor (EMVS)-multiple-input multiple-output (MIMO) radar is an emerging technique that allows for 2D-direction-of-departure (DOD) and 2D-direction-of-arrival (DOA) estimation. Unfortunately, existing array geometries on the EMVS-MIMO radar can rarely reach a good compromise between the estimation accuracy and the computational burden. This article is aimed at proposing an L-shaped sparse array topology for a bistatic EMVS-MIMO radar, whose interelement distance is much larger than half-wavelength. A fast algorithm is proposed herein to estimate the 2D-DOD and 2D-DOA. First, the direction cosine estimates are obtained via the rotational invariance properties of the sparse subarrays, which are ambiguous yet exhibit high-resolution. Thereafter, the direction cosine estimates are achieved via the vector cross-product of the normalized Poynting vectors, which are unambiguous but have low-resolution. The unambiguous high-resolution direction cosine estimates are determined by combining the previous results, following which the 2D-DOD and 2D-DOA can be easily recovered. It is shown that the proposed framework can obtain a better accuracy of estimation than the other existing methods. Moreover, it is more flexible than the current sparse array methodologies. Finally, the theoretical derivations have been validated by simulation results.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
  • SLNR-Based Secure Energy Efficient Beamforming in Multibeam Satellite
           Systems

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      Authors: Zhi Lin;Kang An;Hehao Niu;Yihua Hu;Symeon Chatzinotas;Gan Zheng;Jiangzhou Wang;
      Pages: 2085 - 2088
      Abstract: Motivated by the fact that both security and energy efficiency are the fundamental requirements and design targets of future satellite communications, this letter investigates secure energy efficient beamforming in multibeam satellite systems, where the satellite user in each beam is surrounded by an eavesdropper attempting to intercept the confidential information. To simultaneously improve the transmission security and reduce power consumption, our design objective is to maximize the system secrecy energy efficiency (SEE) under the constraint of total transmit power budget. Different from the existing schemes with high complexity, we propose an alternating optimization scheme to address the SEE problem by decomposing the original nonconvex problem into subproblems. Specifically, we first utilize the signal-to-leakage-plus-noise ratio metric to obtain closed-form normalized beamforming weight vectors, while the successive convex approximation method is used to efficiently solve the power allocation subproblem. Then, an iterative algorithm is proposed to obtain the suboptimal solutions. Finally, simulations are provided to verify the superiority of the proposed scheme compared to the benchmark schemes.
      PubDate: April 2023
      Issue No: Vol. 59, No. 2 (2023)
       
 
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