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Journal Cover
Aerospace and Electronic Systems, IEEE Transactions on
Journal Prestige (SJR): 0.611
Citation Impact (citeScore): 3
Number of Followers: 291  
 
  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: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Optimal Tracking Guidance for Aeroassisted Spacecraft Reconnaissance
           Mission Based on Receding Horizon Control
    • Authors: Runqi Chai;Al Savvaris;Antonios Tsourdos;Senchun Chai;Yuanqing Xia;
      Pages: 1575 - 1588
      Abstract: This paper focuses on the application of model predictive control (MPC) for the spacecraft trajectory tracking problems. The motivation of the use of MPC, also known as receding horizon control, relies on its ability in dealing with control, state, and path constraints that naturally arise in practical trajectory planning problems. Two different MPC schemes are constructed to solve the reconnaissance trajectory tracking problem. Since the MPC solves the online optimal control problems at each sampling instant, the computational cost associated with it can be high. In order to decrease the computational demand due to the optimization process, a newly proposed two-nested gradient method is used and embedded in the two MPC schemes. Simulation results are provided to illustrate the effectiveness and feasibility of the two MPC tracking algorithms combined with the improved optimization technique.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Mixed Mode Radar Coincidence Imaging With Hybrid Excitation Radar Array
    • Authors: Shitao Zhu;Yuchen He;Hongyu Shi;Anxue Zhang;Zhuo Xu;Xiaoli Dong;
      Pages: 1589 - 1604
      Abstract: A novel mixed mode radar coincidence imaging (MMRCI) system, which combines the coherent radar detection and incoherent radar coincidence imaging function during the radar coincidence imaging (RCI) process, is presented in this paper. The target location function of the MMRCI system gives the target position information synchronously with imaging tests, and this makes the MMRCI work independently with low target position estimation error. In the MMRCI system, the resolution of target distance estimation is proportional to the whole bandwidth assisted by the double-frequency linear frequency modulation (DFLFM) signal when the occupied bandwidth of the DFLFM signal is less than one-tenth of the whole bandwidth. The target position estimation error caused by the target motion can be reduced effectively so that the image quality of the moving target can be guaranteed in a longer detection time. The RCI is reconstructed using the incoherent part of the transmitting signal. A general relationship between the spatial correlation of the random radiation field in the imaging plane and the deployments of linear random source is analyzed in the paper. The imaging efficiency is ensured through the grading imaging method based on the imaging requirement. The effectiveness of the MMRCI method is validated via a set of simulations and experiments, including superresolution RCI of both stationary and moving targets in various scenes using the convex optimization algorithms.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Disturbance-Observer-Based Robust Relative Pose Control for Spacecraft
           Rendezvous and Proximity Operations Under Input Saturation
    • Authors: Liang Sun;Wei Huo;Zongxia Jiao;
      Pages: 1605 - 1617
      Abstract: This paper investigates the robust relative pose control for spacecraft rendezvous and proximity operations subject to input saturation, kinematic couplings, parametric uncertainties, and unknown external disturbances. Relative rotational and relative translational nonlinear system models are first derived, and relative attitude and relative position controllers are then proposed, respectively. The kinematic couplings, parametric uncertainties, and unknown external disturbances in dynamical models are treated as compound disturbances, and nonlinear disturbance observers are developed and incorporated into the relative pose control design, which can avoid the assumption on the bounded derivatives of compound disturbances. Meanwhile, input saturation effect of the control torques and forces is compensated by synthesizing the outputs of the auxiliary systems into the controllers. Based on the proposed disturbance observers and auxiliary systems, saturated attitude synchronization and position tracking controllers are developed to reject the unknown compound disturbances and ensure the convergence of the relative pose and velocities. The stability of the closed-loop system is rigorously proved in the Lyapunov framework; relative pose and velocities ultimately converge to the small neighborhoods of the origin in spite of input saturation and model uncertainties. Simulation experiments validate the performance of the proposed robust saturated control strategy.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Overbounding Risk for Quadratic Monitors With Arbitrary Noise
           Distributions
    • Authors: Jason H. Rife;
      Pages: 1618 - 1627
      Abstract: This paper derives equations to bound missed-detection and false-alarm probabilities for a quadratic monitor subject to vector noise with an uncertain, non-Gaussian probability density function (PDF). The bounding equation offers utility for the verification of safety-of-life navigation systems, in terms of both robustness and computational efficiency. Robustness is achieved in that the noise PDF need not be known precisely, so long as the PDF can be appropriately bracketed. Computational efficiency is achieved by transforming non-Gaussian PDFs into a Gaussian form that contributes to fast, repeated evaluations across a great many fault scenarios.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • On Channel Sharing Policies in LEO Mobile Satellite Systems
    • Authors: Ioannis D. Moscholios;Vassilios G. Vassilakis;Nikos C. Sagias;Michael D. Logothetis;
      Pages: 1628 - 1640
      Abstract: We consider a low earth orbit (LEO) mobile satellite system with “satellite-fixed” cells that accommodates new and handover calls of different service-classes. We provide an analytical framework for the efficient calculation of call blocking and handover failure probabilities under two channel sharing policies, namely the fixed channel reservation and the threshold call admission policies. Simulation results verify the accuracy of the proposed formulas. Furthermore, we discuss the applicability of the policies in software-defined LEO satellites.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Adaptive Radon–Fourier Transform for Weak Radar Target Detection
    • Authors: Jia Xu;Liang Yan;Xu Zhou;Teng Long;Xiang-Gen Xia;Yong-Liang Wang;Alfonso Farina;
      Pages: 1641 - 1663
      Abstract: The Radon-Fourier transform (RFT) with a long coherent integration time has recently been proposed for detecting a moving target with an across range cell (ARC) effect. However, without effective clutter suppression, clutter will also be integrated via the RFT, which may affect weak target detection. Based on the maximal signal-to-clutter-plus-noise ratio (SCNR) criteria, a novel adaptive RFT (ARFT) is proposed in this paper to effectively detect a “low-observable” target in a clutter background. The proposed ARFT can combine RFT and adaptive clutter suppression by introducing an optimal filter weight, which is determined from the clutter's covariance matrix as well as a steering vector for a moving target with the ARC effect. In the transformed range-velocity space, the proposed ARFT can suppress background clutter and optimally integrate the target's energy. Nevertheless, with the increase in the integration time, the ARFT needs to address two difficulties in its real implementation. One is the lack of independently and identically distributed (i.i.d.) training samples in a heterogeneous clutter background, and the other is that the computational complexity is too high due to the large number of pulse samples. Therefore, a subaperture ARFT (SA-ARFT) is further proposed in this paper. It divides all coherent pulse samples into several subapertures and accomplishes adaptive clutter suppression in each subaperture. Subsequently, SA-ARFT implements coherent integration among the outputs of different subapertures. The proposed SA-ARFT method can obtain a similar SCNR improvement factor (SCNR IF) with a large number of i.i.d. training samples, while it can obtain a much higher SCNR IF than the ARFT with limited i.i.d. training samples and much lower computational complexity in a heterogeneous clutter background. Finally, some numerical results are provided to demonstrate the effectiveness of the two proposed methods.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Divisible Nonlinear Load Distribution on Heterogeneous Single-Level Trees
    • Authors: Chi-Yeh Chen;Chih-Ping Chu;
      Pages: 1664 - 1678
      Abstract: This work studies the divisible nonlinear load distribution problem on heterogeneous single-level tree networks with a collective communication model. The goal is to find a feasible distribution that minimizes the parallel processing time. The classical model of nonlinear computational loads omits many processing steps, and yields only an approximate solution to distribute fractional loads. This work considers a new model of nonlinear computational loads that includes all of processing steps of the load. This model can simplify recursive equation for the size of fractional loads and yield a practical solution to distribute fractional loads. This work proposes two new methods which incorporates a new nonlinear computational model to distribute a divisible nonlinear load on heterogeneous single-level tree networks. Closed-form expressions for the parallel processing time and speedup for single-level tree networks are derived. This work demonstrates that the asymptotic speed-up of the proposed algorithm ism + 1 where m is the number of child processors in a single-level tree network. We show that our algorithm improved the previous method in terms of speed-up.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Performance Improvement of Time-Balance Radar Schedulers Through Decision
           Policies
    • Authors: Ömer Çayır;Cağatay Candan;
      Pages: 1679 - 1691
      Abstract: The resource management of a phase array system capable of multiple target tracking and surveillance is critical for the realization of its full potential. This paper aims to improve the performance of an existing method, time-balance (TB) scheduling, by establishing an analogy with a well-known stochastic control problem, the machine replacement problem. With the suggested policy, the scheduler can adapt to the operational scenario without a significant sacrifice from the practicality of the TB schedulers. More specifically, the numerical experiments indicate that the schedulers directed with the suggested policy can successfully trade the unnecessary track updates, say of nonmaneuvering targets, with the updates of targets with deteriorating tracks, say of rapidly maneuvering targets, yielding an overall improvement in the tracking performance.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • On the Mitigation of Ionospheric Scintillation in Advanced GNSS Receivers
    • Authors: Jordi Vilà-Valls;Pau Closas;Carles Fernández-Prades;James Thomas Curran;
      Pages: 1692 - 1708
      Abstract: Ionospheric scintillation is one of the major threats and most challenging propagation scenarios affecting Global Navigation Satellite Systems (GNSS) and related applications. The fact that this phenomenon causes severe degradations only in equatorial and high latitude regions has led to very few contributions dealing with the fundamental scintillation mitigation problem, being of paramount importance in safety critical applications and advanced integrity receivers. The goal of this paper is twofold, first to bring together the most relevant contributions on GNSS receiver design under scintillation conditions, and then, to propose a new GNSS carrier tracking framework and scintillation mitigation methodology. Scintillation complex gain components are modeled as AR processes and embedded into the state-space formulation, providing the filter the capability to distinguish between dynamics and phase scintillation contributions. In addition, the actual need of robust solutions is solved by using an adaptive filtering approach and directly operating with the baseband received signal. Simulation results, using both synthetic and real scintillation data, are provided to support the theoretical discussion and to show the performance improvements of such new approach.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Deep convolutional autoencoder for radar-based classification of similar
           aided and unaided human activities
    • Authors: Mehmet Saygın Seyfioğlu;Ahmet Murat Özbayoğlu;Sevgi Zubeyde Gürbüz;
      Pages: 1709 - 1723
      Abstract: Radar-based activity recognition is a problem that has been of great interest due to applications such as border control and security, pedestrian identification for automotive safety, and remote health monitoring. This paper seeks to show the efficacy of micro-Doppler analysis to distinguish even those gaits whose micro-Doppler signatures are not visually distinguishable. Moreover, a three-layer, deep convolutional autoencoder (CAE) is proposed, which utilizes unsupervised pretraining to initialize the weights in the subsequent convolutional layers. This architecture is shown to be more effective than other deep learning architectures, such as convolutional neural networks and autoencoders, as well as conventional classifiers employing predefined features, such as support vector machines (SVM), random forest, and extreme gradient boosting. Results show the performance of the proposed deep CAE yields a correct classification rate of 94.2% for micro-Doppler signatures of 12 different human activities measured indoors using a 4 GHz continuous wave radar-17.3% improvement over SVM.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Automatic Data-Driven Frequency-Warped Cepstral Feature Design for
           Micro-Doppler Classification
    • Authors: Baris Erol;Moeness G. Amin;Sevgi Zubeyde Gurbuz;
      Pages: 1724 - 1738
      Abstract: Micro-Doppler signature analysis and speech processing share a common approach as both rely on the extraction of features from the signal's time-frequency distribution for classification. As a result, features, such as the mel-frequency cepstrum coefficients (MFCCs), which have shown success in speech processing, have been proposed for use in micro-Doppler classification. MFCCs were originally designed to take into account the auditory properties of the human ear by filtering the signal using a filter bank spaced according to the mel-frequency scale. However, the physics underlying radar micro-Doppler is unrelated to that of human hearing or speech. This work shows that the mel-scale filter bank results in the loss of frequency components significant to the classification of radar micro-Doppler. A novel method for frequency-warped cepstral feature design is proposed as a means for optimizing the efficacy of features in a data-driven fashion specifically for micro-Doppler analysis. It is shown that the performance of the proposed frequency warped cepstral coefficients outperforms MFCC based on both simulated and measured data sets for four-class and eight-class human activity classification problems.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Robust Nonlinear Disturbance Observer Based Adaptive Guidance Law Against
           Uncertainties in Missile Dynamics and Target Maneuver
    • Authors: Dongkyoung Chwa;
      Pages: 1739 - 1749
      Abstract: The proposed robust nonlinear disturbance observer based adaptive guidance method considers the nonlinear coupled missile dynamics and rapidly maneuvering target. It also includes unavailable information such as high-order line-of-sight rates and target acceleration as time-varying parametric uncertainties and nonparametric disturbances. An integrated guidance and control model, a robust nonlinear disturbance observer, a nonlinear missile jerk observer, and a robust nonlinear guidance law are proposed, the validity of which is demonstrated by stability analysis and simulations.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Curvature Constrained Cubic Spline Impact Angle Guidance for Intercepting
           Stationary Targets
    • Authors: Ashwin Dhabale;Debasish Ghose;
      Pages: 1750 - 1766
      Abstract: In this paper, a cubic spline guidance law is proposed for intercepting a stationary target at a desired impact angle in surface-to-surface engagement scenarios. An inverse method is used, which represents the altitude as a cubic polynomial of the downrange. The paper addresses many shortcomings of earlier work in this area. In particular, an explicit guidance expression is derived, which makes the guidance law effective and accurate in the presence of disturbances and uncertainties. It is also shown that the guidance command can be obtained using a single cubic spline polynomial even for impact angles greater than and equal to $pi / 2$ , while resulting in substantial improvement in terms of lateral acceleration and length of the trajectory. The paper also obtains an analytically derived capture region. The proposed guidance law is conceptually simple, independent of time-to-go, computationally inexpensive, and does not need linearization.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • A Restricted Bayes Approach to Joint Detection and Estimation Under Prior
           Uncertainty
    • Authors: Berkan Dulek;
      Pages: 1767 - 1782
      Abstract: The problem of joint detection and estimation under prior uncertainty is considered within the framework of restricted Bayes theory, which covers the classical Bayes and minimax frameworks as special cases. A linear combination of the average estimation risk with respect to some guessed prior probability and the maximum conditional estimation risk is minimized for generic convex estimation cost functions subject to a constraint on a linear combination of the average detection error probability with respect to the assumed prior and the maximum conditional detection error probability. Unknown random parameters common to different hypotheses as well as parameters unique to each hypothesis are assumed. The jointly optimal estimators and detector that minimize the resulting estimation performance metric under the detection error constraint are derived. With the proposed framework, it is possible to strike any desired balance between a fully minimax framework (where the worst case performance metrics appear in both the objective and the constraint functions of the optimization problem) and the standard Bayesian setting where exact knowledge of the prior distribution is assumed to be available. Unlike the previous studies in the literature, which deal with special cases of the problem studied in this work, the solution to the most general problem indicates that the optimal estimators are coupled with the optimal detector through a least favorable prior.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Combating Radar Pulse Jamming Using Clipping-Based Noncoherent Pulse
           Integration
    • Authors: Furqan Sadiq Abbasi;Usman Iqbal Ahmed;Sohail Ahmed;
      Pages: 1783 - 1789
      Abstract: A novel pulse integration has been put forward in which the radar receiver, before combining envelope detector outputs in all pulses, first clips them to a suitable level to suppress excessive energy inflicted by a jammer. Mathematical expressions for various decision metrics relevant to this scheme are derived. Using these metrics it is shown that the proposed scheme, when combined with frequency agility, yields healthy performance gain over similar detection schemes when operating against pulse jamming.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Estimation of Higher Order Polynomial Phase Signals in an Impulsive Noise
    • Authors: Igor Djurovic;Marko Simeunović;
      Pages: 1790 - 1798
      Abstract: Parametric estimation of polynomial phase signals (PPSs) corrupted by an impulsive noise has been considered. The interpolation in joint-variable domain has been combined with the hybrid cubic phase function-high-order ambiguity function-based estimator to address this issue. Technique for estimating the percentage of impulses and threshold selection is also proposed. In addition, we propose the refinement procedure to further decrease the mean squared error of PPS parameters estimates.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Performances Analysis of GNSS NLOS Bias Correction in Urban Environment
           Using a Three-Dimensional City Model and GNSS Simulator
    • Authors: Nabil Kbayer;Mohamed Sahmoudi;
      Pages: 1799 - 1814
      Abstract: The well-known conventional least squares (LS) and extended Kalman filter (EKF) are ones of the most widely used algorithms in science and particularly in localization with global navigation satellites systems (GNSS) measurements. However, these estimators are not optimal when the GNSS measurements become contaminated by nonGaussian errors including multipath (MP) and nonline-of-sight (NLOS) biases. On the other hand, this kind of ranging measurements errors occurs generally in urban areas where GNSS-based positioning applications require more accuracy and reliability. In this paper, we use additional information of the environment consisting of bias prediction from a three-dimensional (3-D) model and a GNSS simulator to exploit constructively NLOS measurements. We use this 3-D GNSS simulator to predict lower and upper bounds of these biases. Then, we integrate this information in the position estimation problem by considering these biases as additive error and exploiting the bounds to end-up with a constrained state estimation problem that we resolve with existing constrained least squares (CLS) and constrained EKF (CEFK) algorithms. Experimental results using real GPS signals in down-town Toulouse show that the proposed estimator is capable of improving the positioning accuracy compared with conventional algorithms. Theoretical conditions have been established to determine the acceptable bias prediction error allowing better positioning performance than conventional estimators. Tests are conducted then to validate these conditions and investigate the influence of the bias prediction error on the localization performance by proposing new accuracy metrics.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Secure Distributed Estimation Over Wireless Sensor Networks Under Attacks
    • Authors: Ying Liu;Chunguang Li;
      Pages: 1815 - 1831
      Abstract: The problem of distributed estimation over wireless sensor networks in an adversarial environment with the presence of attacks on sensed and communicated information is considered. To tackle with this problem, a secure diffusion least-mean squares (S-dLMS) algorithm is proposed. The proposed S-dLMS can be considered as a hybrid system, which consists of a noncooperative LMS (nc-LMS) subsystem and a diffusion LMS (dLMS) subsystem. The nc-LMS subsystem is used to provide a reliable reference estimate, which is further used for constructing the threshold test to detect the trust neighbors of each node. Then, based on the detected secure network topology, the dLMS subsystem is performed by combining the received information from the trust neighbors. The performance of the proposed S-dLMS algorithm in the mean and mean-square senses is analyzed, and then an adaptive rule is suggested to select the threshold for detection. Finally, some simulations are performed to show the effectiveness of the proposed S-dLMS algorithm under fixed and time-varying attacks, respectively.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • A Modular Electrical Power System Architecture for Small Spacecraft
    • Authors: Timothy M. Lim;Aaron M. Cramer;James E. Lumpp;Samir A. Rawashdeh;
      Pages: 1832 - 1849
      Abstract: An electrical power system for low-Earth-orbit satellites, which can be reused for a variety of mission requirements with minimal redesign, is proposed. The goals of the proposed power system are achieved by modularizing the subsystems of a small spacecraft and designing them to allow any number of each module to be connected simultaneously. The modularized subsystems include solar energy generation and energy storage. The overall objectives will be accomplished without compromising efficiency or power system stability. The purpose of this paper is to describe the proposed power system and detail the experimental results. The generalized system can be used as a one-size-fits-all solution that only requires basic power systems knowledge to configure and operate.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Knowledge-Aided Bayesian Space-Time Adaptive Processing
    • Authors: Michael Riedl;Lee C. Potter;
      Pages: 1850 - 1861
      Abstract: Ground moving target indicator (GMTI) radar processing attempts to distinguish between radar returns emanating from moving targets and stationary ground clutter. The task is confounded by the relative motion between the radar platform and the scene, as well as by the strength of clutter returns. Techniques such as space-time adaptive processing require an unknown interference covariance describing clutter, jammers, and thermal noise. The covariance is estimated from training data not under test, but, heterogeneous, contaminated, or limited training data degrade the covariance estimate and reduce the detection performance. State-of-the-art techniques for interference covariance estimation reduce the required amount of training data by imposing assumed structure on the covariance matrix. Here, a Bayesian signal model is adopted for jointly estimating targets and clutter in a single cell under test, allowing GMTI processing without training data. The approach incorporates the knowledge of an approximate digital elevation map, platform kinematics (velocity, crab angle, and antenna spacings), and the belief that moving targets are sparse in the scene. Low-complexity computation with the Bayesian model is enabled by recent algorithm developments for fast inference on linear mixing models. Results from the KASSPER I dataset show improved detection performance compared to existing techniques using scores or even hundreds of training bins.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Decreased Probability of Error in Template-Matching Classification Using
           Aspect-Diverse Bistatic SAR
    • Authors: Ellen E. Laubie;Brian D. Rigling;Robert P. Penno;
      Pages: 1862 - 1870
      Abstract: We extend the concept of monostatic aspect diversity for improved automatic target recognition (ATR) to a bistatic synthetic aperture radar (SAR) platform. We derive the probability of error with respect to the number of aspects used for a simple two-target template-matching classification system. The validity of the error prediction is confirmed using simulated bistatic SAR images. Our results demonstrate the ATR benefits of supplementing monostatic SAR images with one or more bistatic SAR images.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Robust Transmitter–Receiver Design in the Presence of
           Signal-Dependent Clutter
    • Authors: Guolong Cui;Yue Fu;Xianxiang Yu;Jian Li;
      Pages: 1871 - 1882
      Abstract: This paper considers the robust transmit-receive design for the detection of a moving point-like target embedded in signal-dependent clutter. In particular, we focus on the phase-only waveforms, sharing either the continuous or the finite alphabet phases and present iterative sequential optimization (ISO) algorithms to sequentially improve the worst-case signal-to-interference-plus-noise ratio (SINR) over clutter statistics. At each iteration, ISO involves multiple fractional programming problems that can be efficiently solved by either Dinkelbach's procedure with closed-form solutions for the continuous phases or the one-dimensional searching method for the discrete phases case. The ISO algorithms enjoy a polynomial complexity in terms of computational burdens. The effectiveness of ISO is confirmed experimentally in terms of the achieved SINR and computational efficiency. Our results also highlight that the design is robust against possible inaccuracies in the prior knowledge of the signal-dependent clutter and even velocity deceptive jamming.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Poisson Multi-Bernoulli Mixture Filter: Direct Derivation and
           Implementation
    • Authors: Ángel F. García-Fernández;Jason L. Williams;Karl Granström;Lennart Svensson;
      Pages: 1883 - 1901
      Abstract: We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multitarget tracking with the standard point target measurements without using probability generating functionals or functional derivatives. We also establish the connection with the δ-generalized labeled multi-Bernoulli (δ-GLMB) filter, showing that a δ-GLMB density represents a multi-Bernoulli mixture with labeled targets soit can be seen as a special case of PMBM. In addition, we propose an implementation for linear/Gaussian dynamic and measurement models and how to efficiently obtain typical estimators in the literature from the PMBM. The PMBM filter is shown to outperform other filters in the literature in a challenging scenario.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Relationship Between Finite Set Statistics and the Multiple Hypothesis
           Tracker
    • Authors: Edmund Brekke;Mandar Chitre;
      Pages: 1902 - 1917
      Abstract: The multiple hypothesis tracker (MHT) and finite set statistics (FISST) are two approaches to multitarget tracking, which both have been heralded as optimal. In this paper, we show that the multitarget Bayes filter with basis in FISST can be expressed in terms the MHT formalism, consisting of association hypotheses with corresponding probabilities and hypothesis-conditional densities of the targets. Furthermore, we show that the resulting MHT-like method under appropriate assumptions (Poisson clutter and birth models, no target death, linear-Gaussian Markov target kinematics) only differs from Reid's MHT with regard to the birth process.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Improved Characterization of GNSS Jammers Using Short-Term Time-Frequency
           Rényi Entropy
    • Authors: Pai Wang;Ediz Cetin;Andrew G. Dempster;Yongqing Wang;Siliang Wu;
      Pages: 1918 - 1930
      Abstract: Availability of global navigation satellite system (GNSS) jammers sold as “personal privacy devices” poses a severe threat to civilian systems that rely on GNSS signals to function. Typically, the large sweep bandwidth of these jammers within a short sweep time makes it difficult to characterize accurately their instantaneous frequency (IF) functions with a view to excising them from the received signal. This results in degraded jammer excision. In this paper, an improved jammer characterization algorithm using time-frequency (TF) analysis is proposed. For the most common chirp-type jammer with one or multi saw-tooth function, short-term Rényi entropy is used to provide information about the turning points in the IF function, which are then used to generate the improved jammer signal IF estimates. Simulation results show that the proposed algorithm alleviates the dominant impulsive-nature IF estimation errors for strong jammers, and thus improves the performance of the IF estimation-based jammer mitigation techniques.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Robust Clutter Rejection in Passive Radar via Generalized Subband
           Cancellation
    • Authors: Jianxin Yi;Xianrong Wan;Deshi Li;Henry Leung;
      Pages: 1931 - 1946
      Abstract: Passive radar is known to suffer from high clutter. In this paper, a generalized subband cancellation (GSC) algorithm is proposed to achieve robust clutter rejection. Four major factors are taken into account, namely carrier frequency offset, sampling frequency offset, fractional delay, and hardware frequency response. The GSC algorithm utilizes subband signal processing and tailored clutter subspace construction to solve the problems caused by these factors. Quantitative evaluations demonstrate that the GSC algorithm approaches the optimal clutter cancellation performance. Its effectiveness is also validated using field experimental data.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • A Multifrequency GPS Signal Strong Equatorial Ionospheric Scintillation
           Simulator: Algorithm, Performance, and Characterization
    • Authors: Yu Jiao;Dongyang Xu;Charles L. Rino;Yu T. Morton;Charles S. Carrano;
      Pages: 1947 - 1965
      Abstract: This paper presents a physics-based, data-consistent, multifrequency GPS scintillation signal simulator. The simulator is based on the two-component power-law phase screen derived from real GPS scintillation measurements. The real data used to initialize the simulator, simulator outputs, and receiver-processed results are compared to demonstrate the simulator accuracy and the receiver processing effects. This simulator will enable better characterization of ionospheric scintillation effects and development of robust receiver algorithms during strong equatorial scintillation.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Adaptive Sensor Selection for Nonlinear Tracking via Sparsity-Promoting
           Approaches
    • Authors: Xiaojun Yang;Ruixin Niu;
      Pages: 1966 - 1982
      Abstract: In this paper, we propose a few sparsity-promoting approaches for sensor selection in wireless sensor networks (WSNs) to reach the optimal tradeoff between the tracking performance and the sensing-communication cost. The proposed framework is valid for general nonlinear target tracking without explicit linearization and not restricted to any specific estimator. We formulate the sensor selection problem as the design of a sparse selection vector. The cardinality of the selection vector is added as a sparsity-promoting penalty term to the cost function where the conditional posterior Cramér-Rao lower bound is used as the criterion for sensor selection. To cope with large-scale WSNs, by combining iterative reweighted ℓ1-norm minimization with the accelerated proximal gradient method and the alternating direction method of multipliers (ADMM), we develop two efficient sensor selection algorithms, respectively. We further develop a low-complexity distributed version of the ADMM where each sensor makes a local sensor selection decision. We test the proposed algorithms by simulations based on an extended Kalman filter using analog data and a particle filter using quantized data, respectively, which provide valuable insights and demonstrate the proposed algorithms' performance.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • ISAR Image Resolution Enhancement: Compressive Sensing Versus
           State-of-the-Art Super-Resolution Techniques
    • Authors: Elisa Giusti;Davide Cataldo;Alessio Bacci;Sonia Tomei;Marco Martorella;
      Pages: 1983 - 1997
      Abstract: The applicability of compressive sensing (CS) to inverse synthetic aperture radar (ISAR) imagery has been widely discussed over the past few years. In particular, CS-based ISAR image-reconstruction algorithms have been developed and their effectiveness proven when dealing with incomplete ISAR data. Resolution enhancement has also been identified as a case for which CS can be effectively applied to ISAR imagery. In this case, the acquired signal can be interpreted as incomplete data in the frequency/slow-time domain and CS used to reconstruct the super-resolved ISAR image. In this paper, an exhaustive performance analysis is carried out along with a comparison between CS and conventional super-resolution techniques. Several concepts and methods have been introduced in order to effectively define the performance, which is not simply based on visual inspection.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Multichannel Cooperative Spectrum Sensing That Integrates Channel Decoding
           With Fusion-Based Decision
    • Authors: Marwan Hadri Azmi;Harry Leib;
      Pages: 1998 - 2014
      Abstract: This paper considers coded multichannel cooperative spectrum sensing (MC-CSS) employing local Neyman-Pearson testing at each sensor and channel decoding integrated with fusion-based decision. A joint multichannel decoding and decision fusion (JMCDDF) algorithm for performing a likelihood ratio test at the fusion center is derived based on the belief propagation technique. For benchmark comparison, we also derive the analytical performance of MC-CSS with error-free reporting channels that do not require channel coding, employing equal decision thresholds at each sensor. Using the JMCDDF algorithm, we compare the performance between uncoded and coded MC-CSS schemes when applying low-density parity-check (LDPC) codes in the presence of reporting channel errors. Monte- Carlo simulation results show considerable performance gains when using the proposed coded MC-CSS schemes. A 3-dB saving in link budget can be achieved by such coded MC-CSS schemes with a short (3, 6) regular LDPC code of codeword length nc = 200, over uncoded MC-CSS. Finally, it is shown that in some cases, protecting the primary user (PU) channels by using variable nodes of higher degrees improves the performance. To equalize the performance for all sensed PU channels, we introduce a simple permutation technique, where, in each transmission, different variable nodes are used to protect local decisions.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • A Signum Polarization Fast Eigen-Based Signal Combining Algorithm
    • Authors: Leiou Wang;Donghui Wang;Chengpeng Hao;
      Pages: 2015 - 2024
      Abstract: Eigen-based algorithms are very effective and stable in signal combining. However, the major problem is the heavy computational cost. In this paper, a fast signal combining algorithm is proposed by using signum polarization and Collatz-Wielandt iteration methods. Simulation results indicate that this algorithm can significantly reduce the computational complexity and has good combining performance.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Generalized Gamma Fading Simulation of Scintillation Disturbed GNSS
           Signals
    • Authors: Fernando Duarte Nunes;Fernando M. Gomes Sousa;
      Pages: 2025 - 2034
      Abstract: The generalized gamma distribution includes as particular cases different well-known distributions, such as the Nakagami-m. We propose a computationally efficient technique to generate correlated time-series with generalized gamma distribution. This method is useful in the simulation of GNSS signals disturbed by ionospheric scintillation. The technique requires only knowledge of two parameters, besides the definition of a model for the amplitude power spectrum.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Target Motion Estimation Ambiguities for Monostatic Synthetic Aperture
           Radar
    • Authors: David Alan Garren;
      Pages: 2035 - 2042
      Abstract: A recent analysis demonstrates that ambiguities exist in attempting to estimate target motion for general bistatic synthetic aperture radar collections. However, monostatic geometries appear to be problematic, since two coordinate angles become indeterminate. The current investigation resolves these issues and provides new insights into the nature of these ambiguities.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Impact Time Control Based on Time-to-Go Prediction for Sea-Skimming
           Antiship Missiles
    • Authors: Min-Jea Tahk;Sang-Wook Shim;Seong-Min Hong;Han-Lim Choi;Chang-Hun Lee;
      Pages: 2043 - 2052
      Abstract: This paper proposes a novel approach for guidance law design to satisfy the impact-time constraints for a certain class of homing missiles. The proposed guidance law provides proper lateral acceleration commands that make the impact time error converge to zero by the time of impact. This scheme can be applied to any existing guidance law for which a formula of predicted time to go is available. Convergence of time-to-go errors is supported by Lyapunov stability. The optimal guidance law and the impact angle control guidance law are extended by the proposed method for impact-time-control guidance and impact-time-and-angle-control guidance, respectively. The performance of the extended guidance laws is demonstrated by numerical simulation.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Fuel-Optimal Low-Thrust Trajectory Optimization Using Indirect Method and
           Successive Convex Programming
    • Authors: Gao Tang;Fanghua Jiang;Junfeng Li;
      Pages: 2053 - 2066
      Abstract: Although the robustness of indirect methods is enhanced by the homotopic approach and switching detection technique when applied to fuel-optimal low-thrust trajectory optimization, the bottleneck in adjoint initialization still needs further investigation. This paper overcomes this bottleneck by the adjoint mapping between the Lagrange multipliers of direct methods to the adjoint variables. The nonconvex optimization problem deduced from direct methods is converted into a convex one by lossless convexification and successive convex programming. By combining these techniques, a framework is built to effectively solve the fuel-optimal low-thrust trajectory optimization problem.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • $acute{text{e}}$+r–Rao+Lower+Bound+Calculation+for+CommSense+System&rft.title=Aerospace+and+Electronic+Systems,+IEEE+Transactions+on&rft.issn=0018-9251&rft.date=2018&rft.volume=54&rft.spage=2067&rft.epage=2074&rft.aulast=Mishra;&rft.aufirst=Abhishek&rft.au=Abhishek+Bhatta;Amit+Kumar+Mishra;">Ambiguity Function and Cram $acute{text{e}}$ r–Rao Lower Bound
           Calculation for CommSense System
    • Authors: Abhishek Bhatta;Amit Kumar Mishra;
      Pages: 2067 - 2074
      Abstract: In our previous work, we have shown that the channel equalization blocks of telecommunication systems can be used to sense the environment, a scheme which we call communication-based sensing (CommSense). The current work presents the ambiguity function analysis for different waveform in passive forward-looking radar geometry for CommSense system. Cramer-Rao lower bound (CRLB) for a two path receive signal model is also calculated for the time delay in the scattered path when there is direct path interference.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Computationally Efficient Bistatic MIMO Radar Signal Processing
           Architecture Based on Coupling of Range and Direction
    • Authors: Hui Li;Yongbo Zhao;Zengfei Cheng;Penglang Shui;Hongtao Su;
      Pages: 2075 - 2085
      Abstract: Since targets located in the same direction of arrival (DOA) have different directions of departure (DOD), the computation burden of signal processing in bistatic multiple-input multiple-output (MIMO) radar is huge. In this paper, a novel computationally efficient signal processing architecture is proposed for bistatic MIMO radar by exploiting the coupling of range and direction (CRD) property. In the proposed architecture, the echo signals of the targets located in the same DOA are processed first using the same space-time matched filter (STMF) without considering the DOD difference. Due to the CRD, the echo signals can be matched efficiently, but the locations of the targets deviate from their true values in the processing result. Then, through analyzing the CRD thoroughly, an iterative method is proposed to rectify the deviation and the targets' real location can be obtained accordingly. Since the echo signals of the targets located in the same DOA can be processed effectively with the same STMF, the proposed architecture is more efficient in computation than the conventional one. The convergence property of the proposed iterative method is guaranteed theoretically, and the effectiveness of the new signal processing architecture is verified through numerical experiments.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • A Fast Gradient-Based Iterative Algorithm for Undersampled Phase Retrieval
    • Authors: Qiang Li;Lei Huang;Wei Liu;Weize Sun;Peichang Zhang;
      Pages: 2086 - 2090
      Abstract: This letter develops a fast iterative shrinkage-thresholding algorithm, which can efficiently tackle the issue in undersampled phase retrieval. First, using the gradient framework and proximal regularization theory, the undersampled phase retrieval problem is formulated as an optimization in terms of least-absolute-shrinkage-and-selection-operator form with (ℓ2 + ℓ1)-norm minimization in the case of sparse signals. A gradient-based phase retrieval via majorization- minimization technique (G-PRIME) is applied to solve a quadratic approximation of the original problem, which, however, suffers a slow convergence rate. Then, an extension of the G-PRIME algorithm is derived to further accelerate the convergence rate, in which an additional iteration is chosen with a marginal increase in computational complexity. Experimental results show that the proposed algorithm outperforms the state-of-the-art approaches in terms of the convergence rate.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Fast Angle Estimation for MIMO Radar With Nonorthogonal Waveforms
    • Authors: Bin Liao;
      Pages: 2091 - 2096
      Abstract: In this letter, a fast angle-estimation method for multiple-input-multiple-output radar with nonorthogonal waveforms is devised. This method first estimates the noise-free covariance matrix by exploiting its low-rank property as well as the sparse structure of the noise-covariance matrix. A subspace-based procedure is then developed to determine the directions-of-arrival (DOAs) based on the matrix composed of the principal eigenvectors of the noise-free covariance-matrix estimate. Compared with the state-of-the-art prewhitening algorithm, the proposed method does not need the knowledge of the correlation matrix of transmitted waveforms. Moreover, it is computationally attractive since the DOAs can be estimated in closed form. In addition, the proposed method offers promising DOA-estimation performance as verified by simulation results.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Technical Areas and Editors: AESS IEEE Aerospace & Electronic Systems
           Society
    • Pages: 2097 - 2102
      Abstract: Lists AESS technical editors and their areas of special interest.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
  • Information for Authors
    • Pages: 2103 - 2104
      Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: Aug. 2018
      Issue No: Vol. 54, No. 4 (2018)
       
 
 
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