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Aerospace and Electronic Systems, IEEE Transactions on
Journal Prestige (SJR): 0.611
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  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9251
Published by IEEE Homepage  [191 journals]
  • IEEE Aerospace and Electronic Systems Society
    • Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Aircraft Landing Using Dynamic Two-Dimensional Image-Based Guidance
           Control
    • Authors: Zhiqi Tang;Rita Cunha;Tarek Hamel;Carlos Silvestre;
      Pages: 2104 - 2117
      Abstract: This paper proposes a two-dimensional (2-D) image-based controller to automatically steer a fixed-wing unmanned aerial vehicle (UAV) during the first three stages of landing: alignment, glide-slope, and flare. Observable image features of the runway and its textured ground are exploited to derive a feedback controller for the automatic maneuver. The proposed controller ensures the horizontal position alignment and a smooth touchdown of the aircraft without estimating the height above the runway. In addition, the 2-D image-based control structure adopted also enforces wind disturbance rejection, without the need for an explicit wind estimator. Simulation results are presented to illustrate the performance of the controller.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Polynomial-Time Methods to Solve Unimodular Quadratic Programs With
           Performance Guarantees
    • Authors: Shankarachary Ragi;Edwin K. P. Chong;Hans D. Mittelmann;
      Pages: 2118 - 2127
      Abstract: We develop polynomial-time heuristic methods to solve unimodular quadratic program (UQP) approximately, which is a known non-deterministic polynomial-time hard (NP-hard) problem. Several problems in active sensing and wireless communication applications boil down to UQPs. First, we derive a performance bound for a known UQP approximation method called dominant eigenvector matching heuristic. Next, we present two new polynomial-time heuristic methods inspired from the greedy strategy, and we provide performance guarantees for these methods with respect to the optimal objective.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Covariance-Based Multiple-Impulse Rendezvous Design
    • Authors: Amir Shakouri;Maryam Kiani;Seid H. Pourtakdoust;
      Pages: 2128 - 2137
      Abstract: A novel trajectory design methodology is proposed in the current work to minimize the state uncertainty in the crucial mission of spacecraft rendezvous. The trajectory is shaped under constraints utilizing a multiple-impulse approach. State uncertainty is characterized in terms of covariance, and the impulse time as the only effective parameter in uncertainty propagation is selected to minimize the trace of the covariance matrix. Furthermore, the impulse location is also adopted as the other design parameter to satisfy various translational constraints of the space mission. Efficiency and viability of the proposed idea have been investigated through some scenarios that include constraints on final time, control effort, and maximum thruster limit addition to considering safe corridors. The obtained results show that proper selection of the impulse time and impulse position fulfills a successful feasible rendezvous mission with minimum uncertainty.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Cochannel Interference in DTMB-Based Passive Radar
    • Authors: Min Lü;Jianxin Yi;Xianrong Wan;Weijie Zhan;
      Pages: 2138 - 2149
      Abstract: This paper discusses the situation with cochannel interferences in the digital television terrestrial multimedia broadcasting (DTMB)-based passive radars. The cochannel interference comes from the station that works in the same frequency with the adopted illuminator of opportunity (IO), but broadcasts different contents. Based on the frame structure of the DTMB signal, the features of the cochannel interference are elaborated. Analyses show that several interfering peaks present in the range-Doppler map when the cochannel interference has the same frame header with the IO. These interfering peaks can be used to identify the existence of cochannel interferences. In addition, to eliminate the influences of the cochannel interference on the target detection, we propose a method that can effectively remove the interfering peaks. The simulation and field experimental results verify the effectiveness of the proposed method.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Partial Consensus and Conservative Fusion of Gaussian Mixtures for
           Distributed PHD Fusion
    • Authors: Tiancheng Li;Juan M. Corchado;Shudong Sun;
      Pages: 2150 - 2163
      Abstract: We propose a novel consensus notion, called “partial consensus,” for distributed Gaussian mixture probability hypothesis density fusion based on a decentralized sensor network, in which only highly weighted Gaussian components (GCs) are exchanged and fused across neighbor sensors. It is shown that this not only gains high efficiency in both network communication and fusion computation, but also significantly compensates the effects of clutter and missed detections. Two “conservative” mixture reduction schemes are devised for refining the combined GCs. One is given by pairwise averaging GCs between sensors based on Hungarian assignment and the other merges close GCs for trace minimal, yet, conservative covariance. The close connection of the result to the two approaches, known as covariance union and arithmetic averaging, is unveiled. Simulations based on a sensor network consisting of both linear and nonlinear sensors, have demonstrated the advantage of our approaches over the generalized covariance intersection approach.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • DNN Transfer Learning From Diversified Micro-Doppler for Motion
           Classification
    • Authors: Mehmet Saygin Seyfioglu;Baris Erol;Sevgi Zubeyde Gurbuz;Moeness G. Amin;
      Pages: 2164 - 2180
      Abstract: Recently, deep neural networks (DNNs) have been the subject of intense research for the classification of radio frequency signals, such as synthetic aperture radar imagery or micro-Doppler signatures. However, a fundamental challenge is the typically small amount of data available due to the high costs and resources required for measurements. Small datasets limit the depth of DNNs implementable, and limit performance. In this work, a novel method for generating diversified radar micro-Doppler signatures using Kinect-based motion capture simulations is proposed as a training database for transfer learning with DNNs. In particular, it is shown that together with residual learning, the proposed DivNet approach allows for the construction of DNNs and offers improved performance in comparison to transfer learning from optical imagery. Furthermore, it is shown that initializing the network using diversified synthetic micro-Doppler signatures enables not only robust performance for previously unseen target profiles, but also class generalization. Results are presented for 7-class and 11-class human activity recognition scenarios using a 4-GHz continuous wave software-defined radar.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Multimodel ELM-Based Identification of an Aircraft Dynamics in the Entire
           Flight Envelope
    • Authors: Seyyed Ali Emami;Alireza Roudbari;
      Pages: 2181 - 2194
      Abstract: The development of a multiple model-based identification algorithm is addressed in this paper for nonlinear modeling of a conventional aircraft in the entire flight envelope. The dynamic model of an aircraft varies significantly depending on changes in the flight condition of the air vehicle including the altitude and the equivalent air speed. Therefore, the conventional identification approaches for generating a single nonlinear model with time-invariant parameters cannot be used in the entire flight envelope of an aircraft. Accordingly, a multiple model-based approach using nonlinear autoregressive exogenous neural networks is introduced in this paper as a powerful tool in identifying complex nonlinear dynamic systems. Different methods of validity function determination are introduced in order to aggregate the separate local models into a single model. The obtained results show that the proposed approach using the extreme learning machine-based validity function determination method has a significant capability to predict the aircraft outputs in various flight conditions. Further, the proposed identification scheme can be used effectively as a precise multistep ahead predictor of nonlinear multivariable systems outputs.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Parameter Estimation Method for Radar Maneuvering Target With Arbitrary
           Migrations
    • Authors: Wei Cui;Shuang Wu;Qing Shen;Jing Tian;Si-Liang Wu;Xiang-Gen Xia;
      Pages: 2195 - 2213
      Abstract: This paper proposes an efficient method for maneuvering targets with arbitrary migrations. This method first employs bisection range frequency conjugate to blindly align the envelopes. Then, the recursively parametric scaled correlation transform is applied to obtain the estimates. The proposed method is free of searching, thus significantly improves the computational efficiency on the premise of retaining the performance. Both simulated and real data verify the effectiveness of the proposed method.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Low-Sidelobe Range-Angle Beamforming With FDA Using Multiple Parameter
           Optimization
    • Authors: Yanhong Xu;Xiaowei Shi;Wentao Li;Jingwei Xu;Lei Huang;
      Pages: 2214 - 2225
      Abstract: In this paper, we propose an equivalent transmit beamforming method in joint range and angle domains at the receiver of the colocated transmit-receive system where frequency diverse array (FDA) acts as transmit antenna. FDA employs a small frequency offset across the array elements and introduces additional degrees-of-freedom in range domain, which can significantly enhance the beamforming flexibility. However, the transmit beampattern of conventional FDA is range-angle-time dependent. In this work, the time-varying problem is first solved by using a series of filters and mixers at the receiver. In the sequel, a subarray-based FDA framework, termed as multisub-FDA, is established and then a range-angle-decoupled equivalent transmit beamforming method is devised based on particle swarm optimization, which incorporates the frequency offset of each subarray and the corresponding weight vector into the optimization problem. With the proposed approach, the array is capable of generating focused beampattern with low sidelobe in both range and angle domains. Numerical results show that the proposed algorithm improves the beamforming performance, range resolution, and sidelobe suppression.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Observer-Based PIGC for Missiles With Impact Angle Constraint
    • Authors: Xianghua Wang;Chee Pin Tan;Donghua Zhou;
      Pages: 2226 - 2240
      Abstract: In this paper, we present an observer-based partial integrated guidance and control (PIGC) scheme for missiles to achieve hit-to-kill attack at a given impact angle. This is particularly useful as the lethality of a missile can be maximized if collision occurs at a certain angle. A novel sliding mode observer is proposed to estimate all states of the system in finite time, from which the PIGC is designed to make all states converge to zero and achieve the objective. The observer parameters are automatically updated by adaptive laws, which removes the requirement of knowing the bound of disturbances and hence making the scheme more applicable to real missile systems.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Power Line Recognition From Aerial Images With Deep Learning
    • Authors: Ömer Emre Yetgin;Burak Benligiray;Ömer Nezih Gerek;
      Pages: 2241 - 2252
      Abstract: Avoidance of power lines is an important issue of flight safety. Assistance systems that automatically detect power lines can prevent accidents caused by pilot unawareness. In this study, we propose using convolutional neural networks (CNN) to recognize the presence of power lines in aerial images. Deep CNN architectures such as VGG and ResNet are originally designed to recognize objects in the ImageNet dataset. We show that they are also successful at extracting features that indicate the presence of power lines, which appear as simple, yet subtle structures. Another interesting finding is that pretraining the CNN with the ImageNet dataset improves power line recognition rate significantly. This indicates that the usage of ImageNet pretraining should not be limited to high-level visual tasks, as it also develops general-purpose visual skills that apply to more primitive tasks. To test the proposed methods’ performance, we collected an aerial dataset and made it publicly available. We experimented with training CNNs in an end-to-end fashion, along with extracting features from the intermediate stages of CNNs and feeding them to various classifiers. These experiments were repeated with different architectures and preprocessing methods, resulting in an expansive account of best practices for the usage of CNNs for power line recognition.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • The Labeled Multi-Bernoulli Filter for Multitarget Tracking With Glint
           Noise
    • Authors: Peng Dong;Zhongliang Jing;Henry Leung;Kai Shen;Minzhe Li;
      Pages: 2253 - 2268
      Abstract: A labeled multi-Bernoulli (LMB) filter is presented to perform multitarget tracking (MTT) for the glint noise. The measurement noise is modeled as a multivariate Student-$t$ process. The variational Bayesian method is applied in the LMB framework with the augmented state. The predictive likelihood is calculated via minimizing the Kullback–Leibler divergence by the variational lower bound. Simulation results show that our approach is effective in MTT with the glint noise.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Performance Analysis of Decision/Data Fusion-Aided Cooperative Cognitive
           Radio Network Over Generalized Fading Channel
    • Authors: Suresh Kumar Balam;P. Siddaiah;Srinivas Nallagonda;
      Pages: 2269 - 2276
      Abstract: In this paper, the analytical performance evaluation of the cooperative cognitive radio network (CCRN) with hard-decision and soft-data fusions is investigated in the presence of noisy and generalized $kappa -mu$ fading channel. The novel expressions to calculate detection probability of CCRN subject to $kappa -mu$ fading and fusion are derived. The analysis of various fusions is evaluated and compared. The performance of CCRN, considering an erroneous sensing and reporting channels, is studied. Also, an optimal threshold subject to fusion scheme is computed. The CCRN performance is evaluated through miss detection probability and total error rate, considering the significant impact of channel and network parameters. Finally, Monte Carlo simulation is performed to validate the derived expressions.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Detection and Tracking of Multipath Targets in Over-the-Horizon Radar
    • Authors: Samuel J. Davey;Giuseppe A. Fabrizio;Mark G. Rutten;
      Pages: 2277 - 2295
      Abstract: In skywave over-the-horizon radar, the ionosphere often supports multiple propagation paths, and a single target can appear as a family of returns. This paper presents two new tracking approaches for this environment: The first uses measurement fusion, and the second uses group-target track-before-detect algorithm. In contrast to previous studies, we find that the biggest benefit is not improved detection sensitivity but rather associating the whole pattern of multipath returns significantly improves the ability to follow maneuvers.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • One-Bit Recursive Least-Squares Algorithm With Application to Distributed
           Target Localization
    • Authors: Zhaoting Liu;Chunguang Li;Zhaoyang Zhang;
      Pages: 2296 - 2313
      Abstract: Adaptation and learning over low-cost wireless networks, meanwhile keeping an acceptable performance, are well motivated. This paper focuses on online parameter estimation over binary networks, which consist of noisy low-resolution sensors, each only giving coarsely one-bit quantized output observations and transmitting them to a fusion center. We develop a class of recursive least-squares (RLS) algorithms based on an expectation–maximization framework, which realizes adaptive parameter estimation from one-bit observations of the noisy output stream. The developed algorithms are, respectively, derived with and without prior knowledge of the noise variances, and their performances are theoretically and experimentally evaluated. Moreover, it is shown that, although the information contained in the one-bit observations is very limited, the proposed algorithms are comparable to the classical RLS algorithm using the original (nonquantized) observations. In addition, as a practical application, the proposed algorithm combined with array signal processing techniques is applied to bearing-only target localization over wireless sensor array networks, and its effectiveness is verified through simulation experiments.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Radar Waveform Optimization for Target Parameter Estimation in Cooperative
           Radar-Communications Systems
    • Authors: Marian Bică;Visa Koivunen;
      Pages: 2314 - 2326
      Abstract: The coexistence between radar and communications systems has received considerable attention from the research community in the past years. In this paper, a radar waveform design method for target parameter estimation is proposed. Target time delay parameter is used as an example. The case where the two systems are not colocated is considered. Radar waveform optimization is performed using statistical criteria associated with estimation performance, namely Fisher Information (FI) and Cramér–Rao Bound (CRB). Expressions for FI and CRB are analytically derived. Optimization of waveforms is performed by imposing constraints on the total transmitted radar power, constraints on the interference caused to the communications system, as well as constraints on the subcarrier power ratio (SPR) of the radar waveform. The frequency-domain SPR is different than the peak-to-average power ratio, which is computed in time domain. It is shown, using simulation results, that the proposed optimization strategies outperform other strategies in terms of estimation error. It is also shown that the SPR constraint reduces the delay domain ambiguities.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • A Novel Method to Detect and Localize LPI Radars
    • Authors: Farzam Hejazikookamari;Yaser Norouzi;Elham Sadat Kashani;Mohammad Mahdi Nayebi;
      Pages: 2327 - 2336
      Abstract: In this study, a new passive method suitable for geolocating low probability of intercept (LPI) radars is introduced. The method uses two electronic support receivers placed on a fast moving platform (e.g., an airplane or a satellite). The proposed method has a high processing gain, which makes it highly suitable for very weak LPI signals. The method processing gain was analytically derived and illustrated with simulation to determine if the proposed method can detect LPI radars in much lower SNRs compared to regular time–frequency LPI detection methods. Also, the resolution of the proposed method in both range and cross-range directions in radar location finding was analyzed. The results showed that the method is capable of radar location finding for complex radars and in complicated electromagnetic environments.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Haptic and Virtual Reality Based Shared Control for MAV
    • Authors: Shafiqul Islam;Reem Ashour;Anderson Sunda-Meya;
      Pages: 2337 - 2346
      Abstract: In this paper, we propose a haptic and virtual reality based shared control with a potential and impedance forces feedback for bilateral shared manipulation of a miniature aerial vehicle (MAV). The interface allows operator for safe navigation, control, and stable interaction between the MAV and a remote environment. The proposed interface is tested on a quadrotor MAV to verify the effectiveness for interaction with the real-world environment.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Predator-Prey Pigeon-Inspired Optimization for UAV ALS Longitudinal
           Parameters Tuning
    • Authors: Haibin Duan;Mengzhen Huo;Zhiyuan Yang;Yuhui Shi;Qinan Luo;
      Pages: 2347 - 2358
      Abstract: This paper presents a predator-prey pigeon-inspired optimization (PPPIO) algorithm for an automatic landing system of a fixed-wing unmanned aerial vehicle (UAV) in the longitudinal plane. A pitch command autopilot and two types of approach power compensators are presented and evaluated in automatic landing. The design of a glide slope command system and an approach power compensator are converted to a finite-dimensional optimization problem. The longitudinal flight controller parameters are optimized by the proposed PPPIO algorithm. The differences between the two proposed approach power compensators are also analyzed. The proposed optimization process can guarantee the control gains vector converge to an approximate optimal solution, and it is computationally much more efficient. Simulation results are presented to demonstrate that this approach helps solve control system optimization problems for different criteria and attains a rather accurate result. As verified by these simulation results, the proposed automatic landing system can help improve UAV's performance during the landing phase.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Comparison of Maximum-Likelihood Estimation and Other Methods for Clutter
           Doppler Centroid Estimation
    • Authors: Shanka N. Wijesundara;Kristine L. Bell;Graeme E. Smith;Andrew O’Brien;Joel T. Johnson;
      Pages: 2359 - 2369
      Abstract: This paper investigates the performance of multiple approaches, including maximum likelihood estimation (MLE), for determining the Doppler frequency of radar returns from clutter scatterers. Fields backscattered from clutter are modeled as a complex stationary random process with a specified temporal correlation function received in the presence of additive thermal noise at a specified clutter-to-noise ratio. The MLE implementation is formulated, and its results are then compared through a simulation study to those obtained from traditional pulse-pair processing and other fast Fourier transform based methods in terms of error statistics and computational complexity. The methods are also compared for measurements of sea clutter from an X-band radar system. The results of the study show that the MLE approach has modest advantages over other methods in certain conditions, but that the performance gains obtained may often be insufficient to justify the extra computational cost or a-priori knowledge requirements of the method.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • ADS-B Anomalies and Intrusions Detection by Sensor Clocks Tracking
    • Authors: Mauro Leonardi;
      Pages: 2370 - 2381
      Abstract: Automatic dependent surveillance-broadcast (ADS-B) is an air traffic control system in which aircraft transmit their own information (identity, position, velocity etc.) to ground sensors for surveillance scope. The tracking of the different sensors’ clocks by the use of time difference of arrival of ADS-B messages is proposed to check the veracity of the position information contained in the ADS-B messages. The method allows detecting possible on-board anomalies or the malicious injection of fake messages (intrusion) without the use of the multilateration (or any other) location algorithm. It follows that it does not need the inversion of the location problem (usually strong nonlinear and ill-posed), and, contrary to the multilateration, it works also with less than four sensors.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Trajectory Planning for Improving Vision-Based Target Geolocation
           Performance Using a Quad-Rotor UAV
    • Authors: Lele Zhang;Fang Deng;Jie Chen;Yingcai Bi;Swee King Phang;Xudong Chen;
      Pages: 2382 - 2394
      Abstract: This paper describes a novel method to improve the target location accuracy through imaging it from an aircraft. This method focuses on improving estimation accuracy of heading angle bias and then to improve geolocation performance. A particle swarm optimization algorithm is employed to derive an expression of optimal trajectory, which can be a guide for trajectory planning. Thanks to the maneuverability of quad-rotor unmanned aerial vehicles, the aircraft is commanded to follow path generated by trajectory planning to acquire multiple bearing measurements of the ground object. The main result is that the aircraft's heading angle bias can be more accurately estimated using trajectory planning. Hence, the target is more accurately geolocated. The efficacy of this technique is verified and demonstrated by simulation results and flight test.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • State Estimation With Trajectory Shape Constraints Using
           Pseudomeasurements
    • Authors: Gongjian Zhou;Keyi Li;Thiagalingam Kirubarajan;Linfeng Xu;
      Pages: 2395 - 2407
      Abstract: In this paper, a trajectory shape constraint on target motion is investigated, and the corresponding state estimation method is presented. This type of constraint occurs when only the shape of the target trajectory is known a priori, without any other necessary information to exactly describe the specific trajectory. For example, one may only know that the target moves along a straight line. This prior knowledge of trajectory can be considered as a constraint to improve tracking performance. To describe the shape constraint arising from the straight line assumption, the state vector is augmented by the states at previous time steps. This facilitates the description of the shape constraint using the components of the state vector. Pseudomeasurements are then constructed based on these relationships to incorporate the constraint into an estimation process to improve the performance. The redundancy of the complete set of pseudomeasurements for a given augmented state vector is analyzed, and the minimal set of pseudomeasurements, which describes the constraint exactly, is proposed. The time evolution equation for the augmented state and the measurement equation using the minimal pseudomeasurement set are formulated. A trajectory shape constraint Kalman filter (TSCKF) is then proposed for simultaneous filtering and smoothing. Since both the measurement vector and the state vector are high dimensional, the cubature Kalman filter is used in the proposed TSCKF to deal with the strong nonlinearity in this problem. Monte Carlo simulations illustrate the effectiveness of the proposed TSCKF and the improvement in both filtering and smoothing accuracies by incorporating the trajectory shape constraint.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Radar Detection of Moderately Fluctuating Target Based on Optimal Hybrid
           Integration Detector
    • Authors: Xu Zhou;Lichang Qian;Zegang Ding;Jia Xu;Weijian Liu;Pengjie You;Teng Long;
      Pages: 2408 - 2425
      Abstract: The optimal detector of the moderately fluctuating model has been shown to be a weighted noncoherent integrator of sampled pulse returns. Nevertheless, the calculation of the optimal weights in the optimal detector needs dynamic inversion of a covariance matrix, which results in huge computation complexity. In this paper, a general description of the hybrid integration detector (HID) for moderately fluctuating target is given to achieve a good balance between detection performance and computation complexity. In the HID, the integration time is divided into several subapertures with coherent integration implemented within each subaperture, with noncoherent integration among subapertures. To obtain the optimal detection performance of the HID, the optimal length of subaperture is derived and theoretical detection threshold is given, based on which an optimal HID (OHID) is proposed for the detection of moderately fluctuating Rayleigh targets in noise background. Furthermore, according to the fluctuation degree which can be reflected by the relationship of detection performance between two special cases of HID, i.e., coherent integration detector and noncoherent integration detector, three kinds of target types are defined, namely, strong, ordinary, and weak fluctuating targets. At the cost of small detection performance loss of these moderately fluctuating targets, the proposed OHID can improve the computation efficiency remarkably. Numerical experiments are provided to demonstrate the effectiveness and efficiency of the proposed method.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Sidelobe Leakage Reduction in Random Phase Diversity Radar Using Coherent
           CLEAN
    • Authors: Paul Berestesky;Elsayed Hesham Attia;
      Pages: 2426 - 2435
      Abstract: Random pulse-to-pulse phase diversity provides the means to suppress range-ambiguous interference in medium-to-high pulse repetition frequency radar applications. However, Doppler filters used in random phase diversity processing tend to suffer from high average sidelobe levels. This paper shows how this problem can be addressed using Coherent CLEAN, a deconvolution algorithm originally developed to address the problem of sidelobe interference in sparse antenna arrays. In the context of random phase diversity, Coherent CLEAN can remove sidelobe leakage from the output of a random phase diversity Doppler filter bank or be applied more directly to disentangle returns from multiple range ambiguities. The algorithm is proposed as an effective and computationally efficient feasible alternative to iterative filter refinement or “worst-case” filter shaping for suppression of unexpected returns. Multiple modes of applying Coherent CLEAN are described and a new variation of the algorithm, simultaneous Coherent CLEAN, is introduced.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Real-Time Optimal Control for Spacecraft Orbit Transfer via Multiscale
           Deep Neural Networks
    • Authors: Lin Cheng;Zhenbo Wang;Fanghua Jiang;Chengyang Zhou;
      Pages: 2436 - 2450
      Abstract: This study is motivated by the requirement of on-board trajectory optimization with guaranteed convergence and real-time performance for optimal spacecraft orbit transfers. To this end, a real-time optimal control approach is proposed using deep learning technologies to obtain minimum-time trajectories of solar sail spacecraft for orbit transfer missions. First, the minimum-time two-dimensional orbit transfer problem is solved by an indirect method, and the costate normalization technique is introduced to increase the probability of finding the optimal solutions. Second, by making novel use of deep learning technologies, three deep neural networks are designed and trained offline by the obtained optimal solutions to generate the guidance commands in real time during flight. Consequently, the long-standing difficulty of on-board trajectory generation is resolved. Then, an interactive network training strategy is presented to increase the success rate of finding optima by supplying good initial guesses for the indirect method. Moreover, a multiscale network cooperation strategy is designed to deal with the recognition deficiency of deep neural networks (DNNs) with small input values, which helps achieve highly precise control of terminal orbit insertion. Numerical simulations are given to substantiate the efficiency of these techniques, and illustrate the effectiveness and robustness of the proposed DNN-based trajectory control for future on-board applications.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • $H_{infty+}$ +Control+for+Spacecraft+Body-Fixed+Hovering+Around+Noncooperative+Target+Via+Modified+ $theta+-D$ +Method&rft.title=Aerospace+and+Electronic+Systems,+IEEE+Transactions+on&rft.issn=0018-9251&rft.date=2019&rft.volume=55&rft.spage=2451&rft.epage=2463&rft.aulast=Jia;&rft.aufirst=Yi&rft.au=Yi+Huang;Yingmin+Jia;">Nonlinear Robust $H_{infty }$ Control for Spacecraft Body-Fixed Hovering
           Around Noncooperative Target Via Modified $theta -D$ Method
    • Authors: Yi Huang;Yingmin Jia;
      Pages: 2451 - 2463
      Abstract: This paper addresses the robust control problem of spacecraft body-fixed hovering near a noncooperative target in the presence of parametric uncertainties and disturbances. A closed-form nonlinear robust $H_{infty }$ controller constructed by the solution of Hamilton–Jacobi–Isaacs (HJI) inequality is designed, which can stabilize the closed-loop system with the $H_{infty }$ performance. To obtain the solution of HJI, an effective numerical approximation approach called the modified $theta text{--}D$ method is proposed, which can obtain a numerical approximation solution of HJI by only solving one algebraic Riccati inequality and several Lyapunov equations rather than a partial differential inequality. The detailed numerical calculation processes of solving the HJI are presented, which shows that the modified $theta text{--}D$ method can be implemented offline with less computational burden. Finally, the effectiveness of the designed robust control scheme is demonstrated via a numerical example.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Application of QGA-BP for Fault Detection of Liquid Rocket Engines
    • Authors: Liang Xu;Songbo Zhao;Ningning Li;Qiang Gao;Tao Wang;Wei Xue;
      Pages: 2464 - 2472
      Abstract: In order to overcome the shortcomings of traditional back propagation (BP) and single genetic algorithm (GA), a method based on quantum GA (QGA) is proposed to optimize the BP neural network for fault detection of liquid rocket engines. In this QGA-BP method, a dynamic improvement strategy is adopted to adjust the rotation angle according to the evolution situation, and a quantum catastrophe strategy is used as an operation criterion during evolution. Then, the improved QGA is used to optimize the weight and threshold of the BP neural network from multiple spots. This method is applied to a typical fault detection process of a liquid rocket engine. Representative history test data of engine state is used to verify this method, and the results show that the convergence speed, the evolution generation, and the accuracy of fault detection of the QGA-BP model are all improved compared with the traditional BP neural network and the single GA.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Efficient Pairing-Free Identity-Based ADS-B Authentication Scheme With
           Batch Verification
    • Authors: Gowri Thumbur;N. B. Gayathri;P. Vasudeva Reddy;Md. Zia Ur Rahman;Aime' Lay-Ekuakille;
      Pages: 2473 - 2486
      Abstract: Automatic dependent surveillance-broadcast (ADS-B) is an emerging air traffic surveillance technology that overcomes the limitations of today's radar technology and enhances the air traffic control. To provide authenticity, integrity in ADS-B and to improve the computation, communications efficiency, in this paper, we propose a new, efficient, and secure pairing-free ADS-B authentication scheme with Batch Verification in ID-based framework. The proposed scheme is proven secure and is more efficient than the existing schemes.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Model Predictive Convex Programming for Constrained Vehicle Guidance
    • Authors: Haichao Hong;Arnab Maity;Florian Holzapfel;Shengjing Tang;
      Pages: 2487 - 2500
      Abstract: A new model predictive convex programming is proposed in this paper for state and input constrained vehicle guidance design. The proposed method defines a convex optimization framework considering a flexibly designed cost function subject to inequality constraints and a sensitivity relation between state increments and input corrections. This formulated convex optimization problem can be solved in a computationally efficient manner. Simulation studies of nonlinear missile and aircraft landing guidance problems demonstrate the effectiveness of the proposed approach.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Kernel LMS-Based Estimation Techniques for Radar Systems
    • Authors: Uday Kumar Singh;Rangeet Mitra;Vimal Bhatia;Amit Kumar Mishra;
      Pages: 2501 - 2515
      Abstract: Relationship between the delay and Doppler shift with the radar return is nonlinear in nature. Therefore, a nonlinear estimator based on sparse kernel least mean square algorithm is proposed. Further, an adaptive kernel width optimization technique is proposed to lower the computational complexity and for simple implementation. An expression for the Cramer–Rao lower bound is derived and validated for the proposed estimator over linear frequency modulated, and orthogonal frequency division multiplexed radar systems.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Deep Learning Based Radio-Signal Identification With Hardware Design
    • Authors: Gihan Janith Mendis;Jin Wei-Kocsis;Arjuna Madanayake;
      Pages: 2516 - 2531
      Abstract: This paper proposes a deep learning based intelligent method for detecting and identifying radio signals considering two applications: first, cognitive radar for identifying micro unmanned aerial systems and second, an automated modulation classification scheme for cognitive radio, which can be used for aeronautical communication systems. Our proposed intelligent method is designed of a spectral correlation function based feature extractor and a low-complexity deep belief network classifier with low FPGA logic utilization.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Improvement of the Long-Term Orbit Prediction for LEO Navigation
           Satellites Using the Inner Formation Method
    • Authors: Zhaokui Wang;Zhendong Hou;Yulin Zhang;
      Pages: 2532 - 2542
      Abstract: In this paper, the concept of the inner formation navigation satellite is proposed. It operates in the low Earth orbit with very high autonomy to make the requirement for ground support minimized. A state transformation matrix-based orbit fitting method is presented for orbit prediction, and the long-term accumulation of prediction errors is investigated by simulations. The fuel consumption for orbit maintaining with a linear controller is discussed. Results show that the orbit can be predicted autonomously to the meter-level accuracy for 90 days if the constant component of residual nongravitational disturbance can be suppressed to $1times 10^{-13},text{m}/ text{s}^{2}$. The maximum fuel consumption for 5 years is on the order of 10 kg if optical sensors and electric thrusters are used for orbit maintaining.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Autonomous Landing Control of Highly Flexible Aircraft Based on Lidar
           Preview in the Presence of Wind Turbulence
    • Authors: Pengyuan Qi;Xiaowei Zhao;Rafael Palacios;
      Pages: 2543 - 2555
      Abstract: This paper investigates preview-based autonomous landing control of a highly flexible flying wing model using short-range light detection and ranging (Lidar) wind measurements in the presence of wind turbulence. The preview control system is developed based on a reduced-order linear aeroelastic model and employs a two-loop control scheme. The outer loop employs the linear active disturbance rejection control and PI algorithms to track the reference landing trajectory and vertical speed, respectively, and to generate the attitude angle command. This is then used by the inner loop using H$_{infty }$ preview control to compute the control inputs to the actuators (control flaps and thrust). A landing trajectory navigation system is designed to generate real-time reference commands for the landing control system. A Lidar simulator is developed to measure the wind disturbances at a distance in front of the aircraft, which is provided to the inner-loop H$_{infty }$ preview controller as prior knowledge to improve control performance. Simulation results based on the full-order nonlinear flexible aircraft dynamic model show that the preview-based landing control system is able to land the flying wing effectively and safely, showing better control performance than the baseline landing control system (without preview) with respect to landing effectiveness and disturbance rejection. The control system's robustness to measurement error in the Lidar system is also demonstrated.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Geometry Error Analysis in Solar Doppler Difference Navigation for the
           Capture Phase
    • Authors: Jin Liu;Xiao-Lin Ning;Xin Ma;Jian-Cheng Fang;
      Pages: 2556 - 2567
      Abstract: Deep space exploration missions continue to become more ambitious, driving the need to investigate autonomous navigation systems that are accurate and timely. The solar Doppler difference navigation is a newly developed and promising celestial autonomous navigation method for use, particularly, in the crucial capture period. In this paper, we present novel analyses for three error sources for the solar Doppler difference navigation from the perspective of geometry, motivated with a Mars deep space exploration example. The geometry error sources include the area overlap rate of the direct and the reflected solar light sources, the spread effects related to the time difference of arrival (TDOA) of light, and the solar rotation Doppler difference error. The area overlap rate and the spread effects of the TDOA can be utilized to assess the overlap degree of the direct source and the reflected source in both space and time. Theoretical analyses and simulation results demonstrate that the direct and the reflected light sources can be accurately approximated as the same source. The solar rotation Doppler difference error is explored using a velocity error model. This model forms a hemi-ellipsoid that can be utilized to compensate the Doppler error caused by the solar rotation. The three errors decline with the deep space explorer approaching Mars, which means that the performance of the solar Doppler difference navigation method continuously improves in the critical capture period. These results can offer a reference for the system design of the solar Doppler difference navigation.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Applying Active Diagnosis to Space Systems by On-Board Control Procedures
    • Authors: Elodie Chanthery;Louise Travé-Massuyès;Yannick Pencolé;Régis De Ferluc;Brice Dellandréa;
      Pages: 2568 - 2580
      Abstract: The instrumentation of real systems is often designed for control purposes and control inputs are designed to achieve nominal control objectives. Hence, the available measurements may not be sufficient to isolate faults with certainty and diagnoses are ambiguous. Active diagnosis formulates a planning problem to generate a sequence of actions that, applied to the system, enforces diagnosability and allows to iteratively refine ambiguous diagnoses. This paper analyzes the requirements for applying active diagnosis to space systems and proposes ActHyDiag as an effective framework to solve this problem. It presents the results of applying ActHyDiag to a real-space case study and of implementing the generated plans in the form of on-board control procedures. The case study is a redundant SpaceWire network where up to six instruments, monitored and controlled by the on-board software hosted in the satellite management unit, are transferring science data to a mass memory unit through SpaceWire routers. Experiments have been conducted on a real physical benchmark developed by Thales Alenia Space and demonstrate the effectiveness of the plans proposed by ActHyDiag.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Statistical Skin-Return Results for Retrodirective Cross-Eye Jamming
    • Authors: Warren Paul du Plessis;
      Pages: 2581 - 2591
      Abstract: The effect of the radar skin return from the platform on which a cross-eye jammer is mounted is significant in many practical cross-eye jamming scenarios. However, all published analyses of skin-return affected cross-eye jamming have significant limitations. These limitations are addressed by deriving equations for the distribution of the cross-eye gain in the presence of skin return. The values of these results are demonstrated by using them to gain insight into how skin return affects cross-eye jamming.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • A Space–Time Graph Based Multipath Routing in Disruption-Tolerant
           Earth-Observing Satellite Networks
    • Authors: Fu Jiang;Qinyu Zhang;Zhihua Yang;Peng Yuan;
      Pages: 2592 - 2603
      Abstract: In this paper, we consider the problem of routing in disruption-tolerant-networking-based earth-observing satellite networks, which are characterized by a frequently changing topology and potentially sparse and intermittent connectivity. To handle the routing challenges posed by these properties, we propose a joined space-temporal routing algorithmic framework for those networks, where the time-varying topology is modeled as a space–time graph leveraging the predictability of satellites’ relative motions. Based on this graph model, we devise a multipath routing algorithm [minimum-cost constrained multipath (MCMP)] to find a feasible set of available routing paths, through which a certain amount of mission data can be transferred back to ground stations within a tolerable delay with a minimum cost. To comparatively evaluate the performance of MCMP, moreover, we design an earliest arrival multipath routing policy (EAMP) algorithm based on the typical contact graph routing algorithm. The performance comparisons among MCMP, EAMP, and direct transfer strategy are simulated and analyzed.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Performance Limits of Cognitive-Uplink FSS and Terrestrial FS for Ka-Band
    • Authors: Kang An;Tao Liang;Gan Zheng;Xiaojuan Yan;Yusheng Li;Symeon Chatzinotas;
      Pages: 2604 - 2611
      Abstract: This paper investigates the performance limits of cognitive-uplink fixed satellite service (FSS) and terrestrial fixed service (FS) operating in the range 27.5–29.5 GHz for Ka-band. In light of standard recommendations from the International Telecommunications Union and a rain-fading channel model, we analyze the interference level at the FS receiver by considering statistical properties of the channel, propagation losses, and antenna patterns. By employing the interference constraint criterion at the FS, an analytical expression for the capacity of the cognitive-uplink FSS is derived, which is useful in understanding the limits in performance and the potential application of the considered coexistence scenario. Simulations are carried out to verify the theoretical derivations and highlight the impact of key parameters on the performance limits.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • On Sparse Channel Estimation in Aeronautical Telemetry
    • Authors: Michael Rice;Christopher Hogstrom;Md. Shah Afran;Mohammad Saquib;
      Pages: 2612 - 2618
      Abstract: This paper examines the application of sparse estimation techniques for the estimation of a discrete-time equivalent multipath channel in the aeronautical telemetry context. The sensing matrix comprises samples of shaped offset QPSK-TG (a continuous phase modulation) based on the pilot bit sequence currently defined in the aeronautical telemetry standard. Representative algorithms from the three broad classes of sparse estimators were examined side by side using computer simulations to estimate the postequalizer bit error rate (BER). Ideal and nonideal frequency offset synchronization were assumed in the simulations. The results show that the performance of the matching pursuit (MP) algorithms seemed to be better suited to this application in the sense that no additional steps were required and the postequalizer BER of the best MP algorithm was slightly better than that of the other sparse estimation techniques. In the case of both ideal and nonideal frequency offset synchronization, the postequalizer BER achieved by the generalized orthogonal MP algorithm was approximately 1.5 dB better than that obtained using the nonsparse-constrained maximum likelihood channel estimate.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Technical Areas and Editors: AESS IEEE Aerospace & Electronic Systems
           Society
    • Pages: 2619 - 2623
      Abstract: Presents a listing of the AESS editors, by technical area of expertise.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
  • Information for Authors
    • Pages: 2624 - 2625
      Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: Oct. 2019
      Issue No: Vol. 55, No. 5 (2019)
       
 
 
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