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  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advanced Materials Technologies     Hybrid Journal   (Followers: 1)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 8)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 9)
Advances in Electronics     Open Access   (Followers: 100)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Microelectronic Engineering     Open Access   (Followers: 13)
Advances in Power Electronics     Open Access   (Followers: 40)
Advancing Microelectronics     Hybrid Journal  
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 28)
Annals of Telecommunications     Hybrid Journal   (Followers: 8)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 16)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal  
Batteries     Open Access   (Followers: 9)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 31)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 2)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 9)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 309)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 2)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 124)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 109)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 103)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elektronika ir Elektortechnika     Open Access   (Followers: 2)
Elkha : Jurnal Teknik Elektro     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access   (Followers: 3)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage     Hybrid Journal   (Followers: 1)
Energy Storage Materials     Full-text available via subscription   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal  
EPJ Quantum Technology     Open Access   (Followers: 1)
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 9)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
IACR Transactions on Symmetric Cryptology     Open Access   (Followers: 1)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 102)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 81)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 57)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 3)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 52)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 4)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 42)
IEEE Open Journal of Circuits and Systems     Open Access   (Followers: 3)
IEEE Open Journal of Industry Applications     Open Access   (Followers: 3)
IEEE Open Journal of the Industrial Electronics Society     Open Access   (Followers: 3)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 77)
IEEE Pulse     Hybrid Journal   (Followers: 5)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 23)
IEEE Solid-State Circuits Letters     Hybrid Journal   (Followers: 3)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 367)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 74)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 64)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 39)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 13)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 46)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 227)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 5)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 75)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 40)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 27)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 80)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 4)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 13)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 79)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 11)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 16)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 36)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 60)
IET Smart Grid     Open Access   (Followers: 1)
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 14)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 12)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
International Journal of Control     Hybrid Journal   (Followers: 11)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Hybrid Intelligence     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 16)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 10)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 25)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 12)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 38)
Journal of Electrical Bioimpedance     Open Access  
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 9)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronic Science and Technology     Open Access   (Followers: 1)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access   (Followers: 2)
Journal of Field Robotics     Hybrid Journal   (Followers: 4)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 189)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 10)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 1)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 3)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 11)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
Journal of Power Electronics     Hybrid Journal   (Followers: 2)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 27)
Journal of Signal and Information Processing     Open Access   (Followers: 8)
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microelectronics and Solid State Electronics     Open Access   (Followers: 28)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal   (Followers: 1)
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 8)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 2)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 11)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
Revue Méditerranéenne des Télécommunications     Open Access  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 57)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Solid State Electronics Letters     Open Access  
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Transactions on Cryptographic Hardware and Embedded Systems     Open Access   (Followers: 2)

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Similar Journals
Journal Cover
IEEE Transactions on Aerospace and Electronic Systems
Journal Prestige (SJR): 0.611
Citation Impact (citeScore): 3
Number of Followers: 367  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9251
Published by IEEE Homepage  [229 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: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Single Space Based Sensor Bias Estimation Using a Single Target of
           Opportunity
    • Authors: Djedjiga Belfadel;Yaakov Bar-Shalom;Peter Willett;
      Pages: 1676 - 1684
      Abstract: Sensor registration refers to the estimation/compensation of systematic (bias) errors, in contrast to the random errors from sensor noise. Various methods have been proposed for bias estimation of multiple optical sensors using common targets of opportunity. However, the proposed solutions required the use of multiple (two or more) optical sensors and the need to solve the data association problem arising from the fusion of measurements from multiple sensors. In order to remove these constraints, we provide in this paper a new methodology using a single exoatmospheric target of opportunity seen in a single satellite borne sensor's field of view to estimate the sensor's biases simultaneously with the state of the target. The satellite-based sensor sees the target from a changing direction as a function of its position, allowing the target in this nonlinear tracking system to be observable. The sensor provides the line of sight (LOS) measurements of azimuth and elevation to the target. Sensor pointing calibration is the key precondition for accurate tracking of a target in a space-based system. Statistical tests on the results of simulations, and the evaluation of the Cramér–Rao lower bound (CRLB) on the covariance of the bias estimates show that this method is statistically efficient.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Multiple Target Tracking Based on Sets of Trajectories
    • Authors: Ángel F. García-Fernández;Lennart Svensson;Mark R. Morelande;
      Pages: 1685 - 1707
      Abstract: We propose a solution of the multiple target tracking (MTT) problem based on sets of trajectories and the random finite set framework. A full Bayesian approach to MTT should characterize the distribution of the trajectories given the measurements, as it contains all information about the trajectories. We attain this by considering multiobject density functions in which objects are trajectories. For the standard tracking models, we also describe a conjugate family of multitrajectory density functions.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Effect Analysis of Antenna Vibration on GEO SAR Image
    • Authors: Teng Long;Tianyi Zhang;Zegang Ding;Wei Yin;
      Pages: 1708 - 1721
      Abstract: Existing effect analyses of antenna vibration (AV) on synthetic aperture radar (SAR) image, which are all aimed for low-earth-orbit SAR and based on the linear trajectory, second-order azimuth spectrum, and range time-invariant as well as azimuth time-variant antenna gain, are not feasible in geosynchronous SAR (GEO SAR), because GEO SAR has an obviously curved trajectory, high-order azimuth spectrum, and two-dimensional (2-D) time-variant antenna gain. To overcome these problems and analyze the effects of AV on GEO SAR image, a modified analysis is proposed in this paper. First, based on the curved trajectory, the high-order ideal echo signal model and the ideal point spread function (PSF) of GEO SAR are, respectively, established and deducted, and the AV that consists of antenna translational vibration (ATV) and antenna rotation motion (ARV) and the 2-D time-variant antenna gain in squint mode are also, respectively, modeled. Then, based on the series expansion, the paired echo theory, and the aforementioned models, the echo signal model affected by ATV, the corresponding PSF affected by ATV, the antenna gain model affected by ARV, and the corresponding PSF affected by ARV are obtained, and the effects of ATV and ARV on GEO SAR image are, respectively, analyzed in detail. Compared with existing effect analyses of AV on SAR image, the modified analysis considers the influences of curved trajectory, high-order azimuth spectrum, and 2-D time-variant antenna gain simultaneously, and it has much more accuracy and adaptability correspondingly. Finally, computer simulations validate the correctness of the proposed analysis.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Micro-Doppler Period Estimation Based on Concentration Statistics of
           Ambiguity Function
    • Authors: Wenpeng Zhang;Yaowen Fu;Jiapeng Yin;
      Pages: 1722 - 1741
      Abstract: Radar micro-Doppler (m-D) signature, which reflects the micromotion dynamic and structural characteristics of radar target with micromotion, has received increasing attention. Most of the existing m-D signature-extraction methods operate in the time domain or the time-frequency domain. Different from these methods, in this paper, an m-D period estimation approach that operates in the ambiguity domain is proposed. Although the ambiguity function (AF) has been widely used in the field of radar signal processing, its application for m-D signal is introduced for the first time. It is proved that the AF of m-D signal exhibits periodicity along the lag axis and has the best concentration when the lag equals to multiples of the m-D period. Based on this, three AF concentration statistics are employed to capture the periodicity and to provide the m-D estimate. The most important property of the AF concentration statistics is that they are (or approximately) invariant to polynomial translations with terms not larger than second order even if the signal is Doppler ambiguous. Numeric simulation and real radar experiments are used to validate the effectiveness of the proposed technique.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • An ADS-B Message Authentication Method Based on Certificateless Short
           Signature
    • Authors: Zhijun Wu;Anxin Guo;Meng Yue;Liang Liu;
      Pages: 1742 - 1753
      Abstract: The automatic dependent surveillance—broadcast (ADS-B) system adopts an open communication mode, and the lack of designed-in security measures in the ADS-B system makes it vulnerable to various types of attacks (jamming, spoofing, etc.). In view of the low-bandwidth and less-data-bit features of the ADS-B, this paper studies the integrity and authenticity of information by signing messages and proposes an ADS-B message authentication method based on certificateless short signature. This method uses short signature and does not require certificate management and has efficient performance. Compared with the existing approach, the computation costs of the proposed method in the signature phase are reduced by 1/2, and the signature length is reduced by 3/4. Additionally, we used the extended NS2 simulation platform to simulate 1090ES data link in different scenarios of the network; the simulation results show that our solution is suitable for minimum operational performance standard of ADS-B.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Wingman-Based Estimation and Guidance for a Sensorless PN-Guided Pursuer
    • Authors: Robert Fonod;Tal Shima;
      Pages: 1754 - 1766
      Abstract: A novel wingman-based estimation and guidance concept is proposed for a sensorless pursuer. The pursuer is guided towards a maneuvering aerial target using proportional navigation (PN) guidance law. The wingman is assumed to acquire bearings-only measurements of the target and to accurately track the wingman–pursuer relative position. The pursuer–target relative states, needed for the pursuer guidance law implementation, are estimated from the available data to the wingman. The proposed state estimator is implemented using extended Kalman filter equations and transformed wingman's measurements into the moving pursuer frame. Analytical observability analysis of the proposed wingman-based measuring concept suggests an optimal wingman trajectory in terms of the wingman–pursuer relative geometry. The resulting wingman trajectory ensures maximum observability of the pursuer–target line-of-sight (LOS) angle, which is a crucial parameter needed for the PN guidance law implementation. The resulting trajectory can be directly related to the well-known LOS guidance concept. Monte Carlo simulation results validate the analytical findings and demonstrate the potential of the proposed concept.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Performance Analysis of Distributed Kalman Filtering With Partial
           Diffusion Over Noisy Network
    • Authors: Vahid Vahidpour;Amir Rastegarnia;Milad Latifi;Azam Khalili;Saeid Sanei;
      Pages: 1767 - 1782
      Abstract: The performance of a partial diffusion Kalman filtering (PDKF) algorithm for the networks with noisy links is studied here. A closed-form expression for the steady-state mean square deviation is then derived and theoretically shown that when the links are noisy, the communication–performance tradeoff, reported for the PDKF algorithm, does not hold. Additionally, optimal selection of combination weights is investigated, and a combination rule along with an adaptive implementation is motivated. The results confirm the theoretical outcome.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Robust Time-Domain Broadband Modal Beamforming for Circular Arrays
    • Authors: Shefeng Yan;
      Pages: 1783 - 1794
      Abstract: Modal beamformer for circular arrays, which is based on a circular harmonics decomposition of the sound field, is flexible for use because it is decoupled from the sensor positions. A time-domain implementation of broadband modal beamformer for circular arrays is presented in this paper. This beamforming structure consists of a real-valued circular harmonics transform and steering unit, followed by a pattern generation unit implemented by a set of real-valued finite impulse response (FIR) filters. The beam pattern is controlled through the FIR filters’ tap weights, whose design is decoupled from beam pattern steering and can be formulated as a constrained optimization problem that can be solved efficiently. Multiple array performance measures such as array gain, sensitivity, mainlobe, and sidelobes can be taken into consideration in beamformer design, which is very important in practical applications. Simulation and experimental results are presented to illustrate the effectiveness of the proposed time-domain broadband modal beamforming approach. Performance comparisons between the proposed and the classical methods in weight coefficients, beam patterns, and quality of audio output are also provided. The results show that the proposed approach possesses high robustness and can achieve good frequency invariance.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Multitarget Joint Delay and Doppler-Shift Estimation in Bistatic Passive
           Radar
    • Authors: Mohammed Rashid;Mort Naraghi-Pour;
      Pages: 1795 - 1806
      Abstract: We study the problem of jointly estimating the delays and Doppler shifts of multiple targets in a bistatic passive radar system when the unknown signal from the illuminator of opportunity (IO) is modeled as a correlated stochastic process. We treat all the delays and Doppler shifts as continuous-valued parameters to avoid straddle loss due to discretization. A computationally efficient method based on the expectation maximization (EM) algorithm is proposed, which breaks up the complex multidimensional maximum likelihood estimation problem into several separate optimization problems, one optimization per target. The algorithm provides estimates of all the targets’ delays and Doppler shifts along with the estimate of the IO signal and each target's component signal in the surveillance channel. The Cramer–Rao lower bound (CRLB) is also derived. Simulation results are presented, where we compare the proposed algorithm with the conventional cross-correlation (CC) estimator, modified CC (MCC) estimator, EM with successive interference cancellation (EM-SIC) estimator, and CRLB. It is shown that when the targets are well separated on the delay-Doppler shift plane, the proposed method outperforms all the estimators. Moreover, when the targets are close in this plane, the CC and EM-SIC estimators fails to distinguish the targets, whereas the proposed method successfully estimates the delays and Doppler shifts and outperforms the MCC in this case as well. Finally as the signal-to-noise ratio increases, the performance of the proposed method approaches that of the CRLB.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • A Space-Time Coded Mills Cross MIMO Architecture to Improve DOA Estimation
           and Its Performance Evaluation by Field Experiments
    • Authors: Cahİt Uğur Ungan;Çağatay Candan;Tolga Ciloglu;
      Pages: 1807 - 1818
      Abstract: Conventional Mills Cross architecture suffers from poor direction-of-arrival angle estimation accuracy in the dimension that the transmitter is aligned. To improve the estimation accuracy, a space-time coded, multiple-input multiple-output (MIMO) direction finding method, with complementary codes is presented. The performance of the suggested MIMO Mills Cross architecture has been evaluated by underwater field experiments. Field experiments confirm the feasibility of the proposed approach and illustrate the performance gains. Since the proposed approach does not require any changes in the conventional Mills Cross hardware, the performance improvement can also be realized by a software reconfiguration for existing legacy systems.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • An Efficient DOA Algorithm for Phase Interferometers
    • Authors: Wei-Yau Horng;
      Pages: 1819 - 1828
      Abstract: The paper presents a comprehensible phase interferometer system which considers the four-element array as a cascade of two three-element subarrays and explores the mechanism how the short subarray resolves the ambiguity of the long subarray in a general manner. The resulted method can estimate the direction of arrival with high resolution while keeping very low ambiguity probability in the presence of noises over a wide field of view and a broadband with low computation complexity.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Sequential Fusion Estimation for Sensor Networks With Deceptive Attacks
    • Authors: Wen-An Zhang;Li Yu;Defeng He;
      Pages: 1829 - 1843
      Abstract: We consider multisensor fusion estimation for sensor networks with deceptive attacks. The approach of sequential fusion is applied to sequentially detect attacks and thereafter fuse attacked data from different sensors to generate optimal state estimates for linear dynamic systems and reveal the relations between the attack rate and the estimation performance. The idea behind the novel approach is that by exploring useful portion of data from different sensors, the integrity of a useful data for accurate state estimation may still be preserved through multisensor fusion even after being attacked. First, a design method is presented for the sequential measurement fusion estimator with attack detections and some useful relations are established between the parameters characterizing the attacks and the measurement fusion estimation performance. Then, a sequential state fusion estimator with attack detections is designed and a compensation strategy is proposed to alleviate the performance degradation caused by attacks. Both simulations and experiments of a target tracking system are presented to demonstrate the effectiveness of the proposed results.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Optimal Attitude Control of a Tethered System for Noncoplanar Orbital
           Transfer Under a Constant Thrust
    • Authors: Guowei Zhao;Liang Sun;Hai Huang;Lei Geng;
      Pages: 1844 - 1855
      Abstract: The problem of an optimal attitude control is studied for a tethered system under a constant thrust in noncoplanar orbital transfer. The contributions of this article mainly include two aspects: first, a noncoplanar orbital transfer scheme and second, a closed-loop optimal control method. Based on a constant thrust, a noncoplanar orbital transfer scheme between two sun-synchronous orbits is proposed, enabling convenient engineering implementation. Compared with existing closed-loop control methods, the hierarchical finite-time attitude tracking control method is presented in the last cycle of the closed-loop optimal control to reduce the error at the final moment. A numerical case of a tethered system in noncoplanar orbital transfer is studied to demonstrate the effectiveness of the proposed control scheme.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • An Initial Orbit Determination Method Using Single-Site Very Short Arc
           Radar Observations
    • Authors: Shuo Zhang;Tuo Fu;Defeng Chen;Shuai Ding;Meiguo Gao;
      Pages: 1856 - 1872
      Abstract: A new initial orbit determination (IOD) method using single-site very short arc radar observations is proposed. The method uses slant range, azimuth, and elevation angles to determine the position vector and uses higher order radial measurements (velocity, acceleration, and jerk) to determine the velocity vector. The IOD accuracy based on the geometric dilution of precision (GDOP) metric is analyzed using a linearization approach. Relations between the GDOP and the observation geometry are investigated under a near-circular constraint and the optimal observation geometry for determining the velocity vector is identified. Monte Carlo simulations are presented for a typical low-Earth orbit satellite under two observation geometry configurations. The results demonstrate that the proposed method is feasible for very short arc initial orbit determination.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Bounding Integrity Risk and False Alert Probability Over Exposure Time
           Intervals
    • Authors: Yawei Zhai;Xingqun Zhan;Boris Pervan;
      Pages: 1873 - 1885
      Abstract: This paper investigates the impact of the autocorrelations of monitor test statistics on navigation integrity and continuity. General analytical methods are rigorously developed to evaluate the actual integrity risk and false alert probability over the exposure interval. Prior to this work, the probabilities computed based on one-sample test have been widely applied in aviation navigation. However, it will be shown that using the one-sample probability may lead to overly optimistic results, because the actual risk can be significantly higher, especially for false alert. The new methods are applied to an example problem of advanced receiver autonomous integrity monitoring. To quantify integrity, a simple but conservative upper bound is derived. As for continuity, both analytical and experimental results show that the actual false alert probability is two orders of magnitude higher than previously thought, due to the time-correlation effects. A feasible solution to mitigate this impact is provided, without degrading navigation availability.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • A New Variable Forgetting Factor and Variable Regularized Square Root
           Extended Instrumental Variable PAST Algorithm With Applications
    • Authors: Shing-Chow Chan;Hai-Jun Tan;Jian-Qiang Lin;
      Pages: 1886 - 1902
      Abstract: This article proposes a square-root (SR) extended instrumental variable (EIV) projection approximation subspace tracking (PAST) algorithm with variable forgetting factor (VFF) and variable regularization (VR). A new local polynomial modeling (LPM) based VFF is proposed by minimizing the mean squares deviation of the EIV linear model and the IV-PAST algorithm. A new variable $ell 2$ regularization term is also derived to reduce the variance of the estimator resulting from possibly ill conditioned covariance matrix at low input signal level. An SR version of the algorithm is developed to improve the numerical stability of the algorithm and avoid the problem of loss of positive definiteness of the inverse covariance matrix. The proposed LOFF-VR-SREIV-PAST algorithm can be implemented by both the conventional EIV-PAST algorithm and numerically more stable hyperbolic rotations. Furthermore, the convergence of the proposed VFF-EIV-PAST algorithm using the ordinary differential equation method is analyzed. Its application to the estimation and tracking of direction of arrival under spatial color sensor noise in both stationary and nonstationary scenarios are presented. Simulations demonstrate that the proposed algorithm yields improved performance over the conventional PAST and EIV-PAST algorithms, especially at medium to low signal-to-noise ratio, which is more frequently encountered in practical situations.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • 3-D Relative Localization of Mobile Systems Using Distance-Only
           Measurements via Semidefinite Optimization
    • Authors: Bomin Jiang;Brian D. O. Anderson;Hatem Hmam;
      Pages: 1903 - 1916
      Abstract: In a network of cooperating unmanned aerial vehicles (UAVs), individual UAVs usually need to localize themselves in a shared and generally global frame. This paper studies the localization problem for a group of UAVs navigating in three-dimensional space with limited shared information, viz., noisy distance measurements are the only type of interagent sensing that is available, and only one UAV knows its global coordinates, the others being GPS denied. Initially, for a two-agent problem, but easily generalized to some multiagent problems, this paper first establishes constraints on the minimum number of distance measurements required to achieve the localization. This paper then proposes a composite algorithm based on semidefinite programming (SDP) in a first step, followed by maximum likelihood estimation using gradient descent on a manifold initialized by the SDP calculation. The efficacy of the algorithm is verified with experimental noisy flight data.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Linearized In-Motion Alignment for a Low-Cost INS
    • Authors: Kedong Wang;Xiaohan Xu;Wei Gao;Jinling Wang;
      Pages: 1917 - 1925
      Abstract: An accurately linearized in-motion alignment with a large heading error is proposed for a low-cost inertial navigation system with the aiding of global positioning system. The linearization is designed for both the coarse and the fine stages in the local level frame. A criterion is constructed to determine the time to switch the alignment from the coarse stage to the fine one automatically. A vehicle test demonstrates that the proposed alignment converges fast and accurately.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Framework for a Perceptive Mobile Network Using Joint Communication and
           Radar Sensing
    • Authors: Md. Lushanur Rahman;J. Andrew Zhang;Xiaojing Huang;Y. Jay Guo;Robert W. Heath Jr;
      Pages: 1926 - 1941
      Abstract: In this paper, we develop a framework for a novel perceptive mobile/cellular network that integrates radar sensing function into the mobile communication network. We propose a unified system platform that enables downlink and uplink sensing, sharing the same transmitted signals with communications. We aim to tackle the fundamental sensing parameter estimation problem in perceptive mobile networks, by addressing two key challenges associated with sophisticated mobile signals and rich multipath in mobile networks. To extract sensing parameters from orthogonal frequency division multiple access and spatial division multiple access communication signals, we propose two approaches to formulate it to problems that can be solved by compressive sensing techniques. Most sensing algorithms have limits on the number of multipath signals for their inputs. To reduce the multipath signals, as well as removing unwanted clutter signals, we propose a background subtraction method based on simple recursive computation, and provide a closed-form expression for performance characterization. The effectiveness of these methods is validated in simulations.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • MIMO Radar With Array Manifold Extenders
    • Authors: He Ren;Athanassios Manikas;
      Pages: 1942 - 1954
      Abstract: This article is concerned with the problem of multitarget parameter estimation in arrayed multiple-input multiple-output (MIMO) radar. In particular, the radar operates in the presence of moving targets, where the parameters of interests to be estimated for each target are the relative delay, Doppler frequency, direction-of-arrival (DOA) and complex path coefficients (or target's radar cross section). Using the novel concept of “array manifold extender,” the dimensionality of the observation space increases from $N$ to $Nmathcal {N}_{mathrm{ext}}$, making the radar more powerful than conventional MIMO radar systems by handling more complex targets and estimating their parameters with increased accuracy. Two “manifold extenders” are proposed in this article in conjunction with a novel spatiotemporal subspace-type framework for estimating the target parameters. The performance of proposed framework is examined using computer simulation studies.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Finite-Horizon Robust Suboptimal Control-Based Impact Angle Guidance
    • Authors: Shashi Ranjan Kumar;Arnab Maity;
      Pages: 1955 - 1965
      Abstract: This paper presents impact angle guidance based on finite-horizon robust optimal control. This approach, a fusion of newly proposed finite-time state-dependent Riccati equation and integral sliding-mode-control, solves finite-horizon tracking problem for input-affine nonlinear systems with specified terminal conditions. It also ensures robustness against external disturbances and uncertainties from beginning. The technique for ensuring specified final-time involves deriving closed-form control expression in terms of approximate solution of differential Riccati equation, which further reduces to solutions of algebraic Riccati and Lyapunov equations. This yields computationally efficient algorithm. To alleviate chattering, the supertwisting algorithm is incorporated with the proposed technique. Guidance strategy is derived after converting impact angle problem to tracking one using the proposed algorithm. Efficacy of the proposed guidance is vindicated for various engagement geometries, and also compared with an existing guidance strategy.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Cooperative Localization of a GPS-Denied UAV Using Direction-of-Arrival
           Measurements
    • Authors: James S. Russell;Mengbin Ye;Brian D. O. Anderson;Hatem Hmam;Peter Sarunic;
      Pages: 1966 - 1978
      Abstract: A GPS-denied unmanned aerial vehicle (UAV) (Agent B) is localized through inertial navigation system alignment with the aid of a nearby GPS-equipped UAV (Agent A), which broadcasts its position at several time instants. Agent B measures the signals’ direction of arrival with respect to Agent B's inertial navigation frame. Semidefinite programming and the orthogonal Procrustes algorithm are employed, and accuracy is improved through maximum likelihood estimation. The method is validated using flight data and simulations. A three-agent extension is explored.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Quadrotor Aggressive Deployment, Using a Quaternion-Based Spherical
           Chattering-Free Sliding-Mode Controller
    • Authors: Hernán Abaunza;Pedro Castillo;
      Pages: 1979 - 1991
      Abstract: This paper introduces a nonconventional approach for autonomous multirotor UAV deployment, in which a quadrotor is aggressively launched through the air with its motors turned off. A continuous quaternion attitude trajectory is proposed to safely recover the vehicle into a hover mode. Then, an operator could take the command or continue a desired mission in the autonomous mode. The controller is a chattering-free sliding mode algorithm based on the geometrical properties of quaternions and axis-angle rotations. Lyapunov theory is used to analyze the system stability. The proposed methodology is validated in real-world indoor and outdoor experiments.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Range and Velocity Estimation Using Kernel Maximum Correntropy Based
           Nonlinear Estimators in Non-Gaussian Clutter
    • Authors: Uday Kumar Singh;Rangeet Mitra;Vimal Bhatia;Amit Kumar Mishra;
      Pages: 1992 - 2004
      Abstract: In this article, we propose kernel maximum correntropy based nonlinear estimators for range and velocity estimation in non-Gaussian clutter and system nonlinearity. The proposed estimators are analyzed for linear frequency modulated and stepped frequency radar systems. Additionally, an adaptive update equation is derived for optimization of the kernel width, which further lowers the dictionary size and the variance of the proposed estimators. For performance evaluation of the proposed estimators, an expression is derived for the Cramer–Rao lower bound using a modified Fisher information matrix.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Reinforcing Transient Response of Adaptive Control Systems Using Modified
           Command and Reference Model
    • Authors: Jing Na;Jun Yang;Guanbin Gao;
      Pages: 2005 - 2017
      Abstract: Although adaptive control has been explored for various aerospace applications, there exists an inherent tradeoff between the convergence of the tracking error and the robustness by using high-gain learning to improve the transient behavior and operation safety. This paper studies novel strategies to enhance the transient response of model reference adaptive control (MRAC) for nonlinear aircraft systems with unmatched dynamics. We first develop a new compensator containing the undesired transient residual error to modify the external command. This can tune the command signal to be tracked to reshape the closed-loop system dynamics, whilst the original tracking objective is retained. Moreover, to diminish the potential high-frequency oscillations induced by the high-gain learning in the adaptive law, we resort to an error feedback term in the reference model to accelerate the convergence of the tracking error. In this new MRAC framework, a higher learning gain could be used to improve the tracking error convergence without triggering oscillations. We prove the closed-loop system stability, analyze the enhanced transient performance and examplify the robustness of the proposed adaptive control system. Two numerical examples with benchmark aircraft models are used to show the effectiveness of the proposed strategies.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Consensus of Multiple Spacecraft Systems Over Switching Networks by
           Attitude Feedback
    • Authors: Tianqi Wang;Jie Huang;
      Pages: 2018 - 2025
      Abstract: In this paper, we further consider the leader-following attitude consensus problem of multiple rigid body systems subject to jointly connected switching networks by a distributed attitude feedback control law. Since the network is switching, the closed-loop system is discontinuous. We overcome this difficulty by a generalized Barbalat's lemma. Moreover, we remove two restrictive assumptions in the literature. As a result, our control law is fully distributed and the result is global.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Enabling Robust State Estimation Through Measurement Error Covariance
           Adaptation
    • Authors: Ryan M. Watson;Jason N. Gross;Clark N. Taylor;Robert C. Leishman;
      Pages: 2026 - 2040
      Abstract: Accurate platform localization is an integral component of most robotic systems. As these robotic systems become more ubiquitous, it is necessary to develop robust state-estimation algorithms that are able to withstand novel and noncooperative environments. When dealing with novel and noncooperative environments, little is known a priori about the measurement error uncertainty; thus, there is a requirement that the uncertainty models of the localization algorithm be adaptive. In this paper, we propose the batch covariance estimation technique, which enables robust state estimation through the iterative adaptation of the measurement uncertainty model. The adaptation of the measurement uncertainty model is granted through nonparametric clustering of the residuals, which enables the characterization of the measurement uncertainty via a Gaussian mixture model. The provided Gaussian mixture model can be utilized within any nonlinear least squares optimization algorithm by approximately characterizing each observation with the sufficient statistics of the assigned cluster (i.e., each observation's uncertainty model is updated based on the assignment provided by the nonparametric clustering algorithm). The proposed algorithm is verified on several Global Navigation Satellite System collected datasets, where it is shown that the proposed technique exhibits some advantages when compared to other robust estimation techniques when confronted with degraded data quality.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Receiver Operating Characteristics for a Prototype Quantum Two-Mode
           Squeezing Radar
    • Authors: David Luong;C. W. Sandbo Chang;A. M. Vadiraj;Anthony Damini;Christopher M. Wilson;Bhashyam Balaji;
      Pages: 2041 - 2060
      Abstract: We built and evaluated a prototype quantum radar, which we call a quantum two-mode squeezing (QTMS) radar, in the laboratory. It operates solely at microwave frequencies; there is no downconversion from optical frequencies. Because the signal generation process relies on quantum mechanical principles, the system is considered to contain a quantum-enhanced radar transmitter. This transmitter generates a pair of entangled microwave signals and transmits one of them through free space, where the signal is measured using a simple and rudimentary receiver. At the heart of the transmitter is a device called a Josephson parametric amplifier, which generates a pair of entangled signals called two-mode squeezed vacuums at 6.1445 and 7.5376 GHz. These are then sent through a chain of amplifiers. The 7.5376 GHz beam passes through 0.5 m of free space; the 6.1445 GHz signal is measured directly after amplification. The two measurement results are correlated in order to distinguish signal from noise. We compare our QTMS radar to a classical radar setup using conventional components, which we call a two-mode noise (TMN) radar, and find that there is significant gain when both systems broadcast signals at $-$82 dBm. This is shown via a comparison of receiver operating characteristic curves. In particular, we find that the quantum radar requires eight times fewer integrated samples compared to the TMN radar to achieve the same performance.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • iNavFIter: Next-Generation Inertial Navigation Computation Based on
           Functional Iteration
    • Authors: Yuanxin Wu;
      Pages: 2061 - 2082
      Abstract: Inertial navigation computation is to acquire the attitude, velocity, and position information of a moving body by integrating inertial measurements from gyroscopes and accelerometers. Over half a century has witnessed great efforts in coping with the motion noncommutativity errors to accurately compute the navigation information as far as possible, so as not to compromise the quality measurements of inertial sensors. Highly dynamic applications and the forthcoming cold-atom precision inertial navigation systems demand for even more accurate inertial navigation computation. The paper gives birth to an inertial navigation algorithm to fulfill that demand, named the iNavFIter, which is based on a brand-new framework of functional iterative integration and Chebyshev polynomials. Remarkably, the proposed iNavFIter reduces the noncommutativity errors to almost machine precision, namely, the coning/sculling/scrolling errors that have perplexed the navigation community for long. Numerical results are provided to demonstrate its accuracy superiority over the state-of-the-art inertial navigation algorithms at affordable computation cost.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • A Multidimensional TDOA Association Algorithm for Joint Multitarget
           Localization and Multisensor Synchronization
    • Authors: Tongyu Ge;Ratnasingham Tharmarasa;Bernard Lebel;Mihai Florea;Thiagalingam T. Kirubarajan;
      Pages: 2083 - 2100
      Abstract: This article considers the problem of multitarget localization using time difference of arrival (TDOA) measurements at multiple sensors with misaligned clocks in the presence of data association uncertainty. Sensor synchronization and data association are two essential steps in target localization and tracking to align sensor clocks and to associate measurements from different sensors. In practice, sensor synchronization errors can adversely affect data association performance and vice versa. Although these two processes affect each other, they are usually addressed separately. We propose a novel joint multidimensional association algorithm for multisensor synchronization (JMDA4MS), which performs data association and yields sensor clock offset and target position estimates simultaneously using TDOA measurements. Considering the observability of the unknown parameters, the joint multiframe multidimensional association algorithm is developed as a multiframe extension of the JMDA4MS algorithm. A gating method and a multidimensional plus sequential two-dimensional association approach are utilized to improve the efficiency of the proposed algorithms. The Cramér–Rao lower bound for the proposed maximum likelihood estimator is derived as a performance benchmark. Computer simulations are carried out to evaluate the performance of the proposed algorithms on different scenarios.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Moving Horizon Estimation of Air Data Parameters for UAVs
    • Authors: Andreas Wenz;Tor Arne Johansen;
      Pages: 2101 - 2121
      Abstract: Local wind velocities, angle of attack, and lift coefficients of a fixed-wing unmanned aerial vehicle (UAV) are estimated by fusing kinematic, aerodynamic, and stochastic wind models with data from an inertial measurement unit, a global navigation satellite system receiver, and a pitot-static tube in a moving horizon estimator. Experimental validation with two different UAVs and two sensor sets of different quality shows promising results for both wind velocity and angle of attack estimation.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Robust Gain-Scheduled Flight Controller for an In-Flight Simulator
    • Authors: Masayuki Sato;
      Pages: 2122 - 2135
      Abstract: In-Flight Simulators (IFSs) require flight controllers, which mimic other aircraft's dynamics in a certain operation range, which is the problem addressed in this paper. The design problem of a linear parameter-varying type gain-scheduled flight controller, which simultaneously suppresses gust effect and reproduces low-and-middle frequency commands as IFS's motions in a certain speed range, for the lateral-directional motions of an airplane is addressed via linear matrix inequality formulation. Our controller performance is examined by flight tests.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Joint Target Detection and Tracking in Multipath Environment: A
           Variational Bayesian Approach
    • Authors: Hua Lan;Shuai Sun;Zengfu Wang;Quan Pan;Zhishan Zhang;
      Pages: 2136 - 2156
      Abstract: We consider multitarget detection and tracking problem for a class of multipath detection system where one target may generate multiple measurements via multiple propagation paths, and the association relationship among targets, measurements, and propagation paths is unknown. In order to effectively utilize multipath measurements from one target to improve detection and tracking performance, a tracker has to handle high-dimensional estimation of latent variables including target existence state, target kinematic state, and multipath data association. Based on variational Bayesian inference, we propose a novel joint detection and tracking algorithm that incorporates multipath data association, target detection, and target state estimation in a unified Bayesian framework. The posterior probabilities of these latent variables are derived in a closed-form iterative manner, which is effective for reducing the performance deterioration caused by the coupling between estimation errors and identification errors. Loopy belief propagation is exploited to approximately calculate the probability of multipath data association, saving the computational cost significantly. Simulation results of over-the-horizon radar multitarget tracking show that the proposed algorithm outperforms multihypothesis multipath track fusion and multidetection (hypothesis-oriented) multiple hypothesis tracker, especially under low signal-to-noise ratio circumstance.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • A Machine Learning Approach for Estimating Air Data Parameters of Small
           Fixed-Wing UAVs Using Distributed Pressure Sensors
    • Authors: Kasper Trolle Borup;Thor Inge Fossen;Tor Arne Johansen;
      Pages: 2157 - 2173
      Abstract: This paper presents a method for estimating the air data parameters for a small fixed-wing, unmanned aerial vehicle (UAV) using an arrangement of low-cost Micro-electromechinal systems (MEMS)-based pressure sensors embedded in the surface of the UAV. The pressure measurements are used in a machine learning (ML) model to estimate the angle of attack, sideslip angle, and airspeed. Two ML algorithms based on artificial neural networks (NNs) and linear regression (LR) are implemented, tested, and assessed using data collected from wind tunnel experiments and a flight test, and the results are compared to a benchmark flight test. Training the ML algorithms using wind tunnel data was found to introduce several potential error sources that need to be addressed in order to provide accurate estimation on the benchmark flight test, whereas training the algorithms using flight data provides lower estimation RMSE values. The performance of the NN structures has been found to slightly outperform the LR algorithms in estimation accuracy. Finally, results from using different sensor configurations and a pseudo-Reynolds number are presented in an effort to evaluate the influence of sensor number and placement on the accuracy of the method.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Improved Model for Micro-UAV Propulsion Systems: Characterization and
           Applications
    • Authors: Luis Amezquita-Brooks;Diana Hernandez-Alcantara;Carlos Santana-Delgado;Roberto Covarrubias-Fabela;Octavio Garcia-Salazar;Abigail M. E. Ramirez-Mendoza;
      Pages: 2174 - 2197
      Abstract: An improved propulsion model for multirotor small unmanned aerial vehicles is developed by incorporating the effects of airflow speed, direction, rotor interaction, and other phenomena related to particular configurations, which are elements that are lacking in typical models. Two applications are presented. The first is a propulsion envelope, which helps determining safe operating conditions for particular propulsion systems. The second application allows elucidating important dynamical phenomena that traditional models lack, including possible instability with closed-loop controllers.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Refocusing of Moving Targets Based on Low-Bit Quantized SAR Data via
           Parametric Quantized Iterative Hard Thresholding
    • Authors: Jianghong Han;Gang Li;Xiao-Ping Zhang;
      Pages: 2198 - 2211
      Abstract: Low-bit quantization of echo improves storage and leads to more efficient downlink transmission of spaceborne synthetic aperture radar (SAR) systems. In this paper, a new parametric quantized iterative hard thresholding (PQIHT) algorithm is proposed to refocus the images of moving targets with low-bit quantized SAR data, based on the combination of quantized iterative hard thresholding (QIHT) and the parametric sparse representation. The blurred and quantization-error-involved subimage of the region of interest (ROI) containing the moving target is represented in a sparse fashion through an adaptive parametric dictionary. The QIHT with a pruned searching method is performed for efficiently estimating the motion-adaptive parameter inside the dictionary, refocusing the ROI image and suppressing the quantization-induced error in an iterative way. Different from the conventional QIHT algorithm with a fixed dictionary that can only represent stationary targets, the proposed method exploits a parametric dictionary with a parameter related to target motion status, which is capable of adaptively representing the radar echo from a moving target with unknown motion status and, therefore, is suitable for moving target refocusing. Simulations and experiments on real GF-3 satellite SAR data demonstrate that, compared with the conventional parametric sparse representation framework for moving target refocusing based on purely precise data, the proposed algorithm can provide satisfactory quality of moving target refocusing with remarkably reduced data volume.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • A Hierarchical Fuzzy-Optimal Strategy for Station-Keeping Maneuver of a
           GEO Satellite
    • Authors: Hossein Maghsoudi;Amirreza Kosari;Mahdi Fakoor;Masoud Khoshsima;
      Pages: 2212 - 2227
      Abstract: In order to achieve the best possible performance for an artificial satellite, its position and attitude must be maintained within predetermined limits. This is of great importance, especially in the presence of environmental disturbances and system uncertainties. Therefore, performing correction maneuvers is inevitable. This article puts forward a new hierarchal strategy based on fuzzy logic and optimal control theories for correcting the orbital parameters of a geostationary satellite affected by environmental disturbances. The strategy consists of two successive systems referred to as decision-making and optimizing systems. These systems, based on the assessments performed on position and velocity deviations from the nominal reference trajectory, determine the appropriate moments to fire thrusters and their action durations. In this research, the first task, i.e., determining the firing moments of thrusters was accomplished using a fuzzy logic supervisory system. On the other hand, the second task was performed with a direct optimization method based on minimum-fuel station-keeping criterion while considering the constraints of station-keeping problem. The proposed strategy was applied on a geostationary satellite and for a period of 30 days of its motion, and both north–south and east–west orbital corrections were performed. The results obtained from the simulation analysis indicated that the proposed strategy effectively improved the orbital correction procedure of the satellite in the station-keeping mode.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Robust Distributed Parameter Estimation of Nonlinear Systems With Missing
           Data Over Networks
    • Authors: Sicong Chen;Ying Liu;
      Pages: 2228 - 2244
      Abstract: Distributed parameter estimation of linear systems has received much attention in the past two decades. However, the complicated dynamics of some real systems is difficult to characterize with linear models. Nonlinear models, may instead, be good candidates for complex system modeling. But, due to the nonlinearity of the systems, the existing distributed parameter estimation algorithms are not directly applicable. Besides, due to various physical and man-made reasons, some measurements are missing in practice. Considering this, in this article, two robust distributed estimation algorithms are proposed for estimating the parameters of nonlinear Hammerstein systems with missing data. In the proposed algorithms, a Bayesian hypothesis testing is used to justify whether the incoming measurement is missing or not. Then, the parameters are updated and combined via an adaptive combiner according to the status of the measurements. The performance of the proposed algorithms is analyzed theoretically and verified by some simulations. Results show that the proposed algorithms are very robust to different probabilities of data missing. Although the convergence rates of the proposed algorithms decrease as the probability of data missing increases, the performance of estimation approaches the case when there is no data missing.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Target Positioning With Surveillance Radar by the Estimation of
           Atmospheric Refractivity Profile
    • Authors: Hyukjung Lee;Taeseung Lee;Joohwan Chun;Jonghyun Lee;
      Pages: 2245 - 2255
      Abstract: The positioning of a target with radar measurements could be inaccurate because of the atmospheric refraction effects. We present a technique for determining the refractivity parameters using known position information of cooperative targets. The estimated refractivity parameters are then used to find the position of a noncooperative target, along with its radar range and angle measurements. The performance of the proposed algorithm is assessed by comparing the mean squared error of the estimate with the Cramer–Rao lower bound as well as by testing the algorithm with real field data. Ground-based military surveillance radar can adopt the proposed algorithm and benefit when there are some cooperative flying aircraft while there is no external refractivity information such as radiosonde data.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Exactly Decoupled Kalman Filtering for Multitarget State Estimation With
           Sensor Bias
    • Authors: Jianxin Yi;Xianrong Wan;Deshi Li;
      Pages: 2256 - 2271
      Abstract: The problem of multisensor multitarget state estimation in the presence of constant but unknown sensor biases is investigated. The classical approach to this problem is to augment the state vector to include the states of all the targets and the sensor biases, and then implement an augmented state Kalman filter (ASKF). In this article, we propose a novel decoupled Kalman filtering algorithm. The decoupled Kalman filtering first processes each target in a separate branch, namely the single-target Kalman filtering branch, where the single-target states and the sensor biases are estimated. Then the bias estimate is refined by fusing the former bias estimates across all the single-target Kalman filtering branches. Finally, the refined bias estimate is fed back to each single-target Kalman filtering branch to improve the target state estimation. We prove that the proposed decoupled Kalman filtering is exactly equivalent to the ASKF in terms of the estimation results under a usual initial condition. The equivalence is also confirmed via the numerical example. Moreover, we further validate the proposed algorithm using the field experimental data of a multistatic passive radar.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • A Novel Two-Step Validation Algorithm for Lost-in-Space Star
           Identification
    • Authors: Xiaochu Wang;Changhao Sun;Ting Sun;
      Pages: 2272 - 2279
      Abstract: Since star identification algorithms most likely yield multiple matching candidates, validation algorithms are required for star trackers. Traditional validation is performed in an iteratively cascaded way by incrementally introducing new star points for help, costing plenty of inefficient lookups and complex combinations, but leading to nondeterministic results only. Focusing on this problem, this paper considers a novel validation idea that the attitude estimate perturbation caused by bounded measuring noises should be bounded as well. As a result, a two-step validation algorithm is proposed following a noniterative deterministic structure. Theoretical analyses and simulation examples are both given to demonstrate the algorithm.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Study on Estimation Errors in ZUPT-Aided Pedestrian Inertial Navigation
           Due to IMU Noises
    • Authors: Yusheng Wang;Andrei Chernyshoff;Andrei M. Shkel;
      Pages: 2280 - 2291
      Abstract: We present a study on the effects of the inertial measurement unit (IMU) noises on the navigation solution uncertainty during zero-velocity-update (ZUPT)-aided pedestrian inertial navigation. The analytically derived attitude, velocity, and position propagation errors reveal that among many IMU noise terms, the dominant factor affecting the accuracy of ZUPT-aided pedestrian navigation is rate random walk of gyroscopes. A numerical simulation has been conducted, showing the discrepancy of less than 10% between the numerical and analytical results, supporting fidelity of the analytical estimates. Experiments have also been conducted, and the results were on the same level of analytical and numerical predictions. This article offers a closed-form analytical prediction for the errors of ZUPT-aided pedestrian inertial navigation due to IMU noises.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Classification of Electronic Devices With Power-Swept Signals Using
           Harmonic Radar
    • Authors: Harun Taha Hayvaci;Handan Ilbegi;Imam Samil Yetik;
      Pages: 2292 - 2301
      Abstract: A novel approach for classification of electronic devices using a harmonic radar is proposed in this article. We transmit single-tone time-varying signals with varying power to the electronic circuits under test (ECUTs). The novelty of the proposed approach stems from representing the harmonic response of the ECUT in the harmonic and statistical feature spaces. Besides, as a new approach, we sweep the transmitting power to capture the nonlinear behavior relevant to nonlinear $Itext{--}V$ characteristics of the ECUT. Furthermore, we utilize both the time and frequency content of the received harmonic response. Statistical and Fourier domain features of the received power levels at harmonic frequencies are determined and used for classification. $k$-nearest neighbors is chosen as the classification method. We demonstrate the effectiveness of our method in the presence of noise through Monte Carlo simulations with different signal-to-noise ratio values. Extensive simulation studies show that our new approach of power-swept signals and new features we have developed are very effective at classifying nonlinear devices.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Optimal Post-Detection Integration Techniques for the Reacquisition of
           Weak GNSS Signals
    • Authors: David Gómez-Casco;José A. López-Salcedo;Gonzalo Seco-Granados;
      Pages: 2302 - 2311
      Abstract: This article tackles the problem of finding the optimal noncoherent detector for the reacquisition of weak global navigation satellite system (GNSS) signals in the presence of bits and phase uncertainty. Two solutions are derived based on using two detection frameworks: the Bayesian approach and the generalized likelihood ratio test (GLRT). We also derive approximate detectors of reduced computation complexity and without noticeable performance degradation. Simulation results reveal a clear improvement of the detection probability for the proposed techniques with respect to the conventional detectors implemented in high sensitivity GNSS (HS-GNSS) receivers to acquire weak GNSS signals. Finally, we draw conclusions on which is the best technique to reacquire weak GNSS signals in practice considering a trade-off between performance and complexity.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Capturability of a Sliding-Mode Guidance Law With Finite-Time Convergence
    • Authors: Ke-Bo Li;Hyo-Sang Shin;Antonios Tsourdos;
      Pages: 2312 - 2325
      Abstract: Using the Lyapunov-like approach, the capturability of a recently proposed sliding-mode guidance law, which is used for exoatmospheric interception and can guide the line-of-sight (LOS) angular rate to converge to zero or its small neighborhood in a finite time, is thoroughly analyzed. The target is assumed to have an arbitrary but upper-bounded maneuvering acceleration. A more realistic definition of capture is considered. The upper bound of the commanded acceleration is obtained and so is the capture region. The new theoretical findings are extended to the three-dimensional space with the help of the rotating LOS coordinate system.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Interference-Aware Cognitive Radar: A Remedy to the Automotive
           Interference Problem
    • Authors: Gor Hakobyan;Karim Armanious;Bin Yang;
      Pages: 2326 - 2339
      Abstract: With the advancement of autonomous driving, the number of automotive radar sensors grows dramatically. As a result, interference becomes a major issue that has a vital importance for the future of automotive radar. Parallel to this development, radar concepts based on the digital signal generation and processing such as orthogonal frequency-division multiplexing (OFDM) have been studied over the past few years. The realization of the radar functionality based on digital waveforms provides a large degree of flexibility as well as adaptability. Among others, this can be used for increasing the interference robustness of digital radar systems compared to the traditional automotive radar. In this article, we propose a novel approach to mitigating automotive radar interference based on cognitive interference avoidance, which we demonstrate for the digital OFDM radar. We introduce the main building blocks of such a cognitive radar and focus specifically on waveform adaptation. The proposed waveform adaptation methods enable dynamical adjustment to interference, including adaptation during a single measurement cycle. The feasibility and performance of the proposed concepts are studied in simulations and validated using measurements with an OFDM radar prototype.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Computationally Efficient Estimation of Compound K-Distribution Sea
           Clutter in Thermal Noise and Its Application to Sea Echo Reflectivity
           Observations
    • Authors: Judith A. Northrop;Antonia Papandreou-Suppappola;
      Pages: 2340 - 2350
      Abstract: We consider the parameter estimation of the K-plus-noise distribution model of sea clutter intensity single-pulse observations with unknown thermal noise power. We propose two methods that yield comparable estimation accuracy to existing methods while improving computational cost for real-time processing. These methods iteratively integrate one-dimensional nonlinear curve fitting with integer and fractional intensity moment computations. We provide numerically computed Cramér–Rao lower bounds for the shape estimate as a bench mark for asymptotically unbiased estimators. Performance is demonstrated using simulations and two high-resolution sea echo reflectivity datasets.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Comprehensive Time-Offset Estimation for Multisensor Target Tracking
    • Authors: Song Li;Yongmei Cheng;Daly Brown;Ratnasingham Tharmarasa;Gongjian Zhou;Thia Kirubarajan;
      Pages: 2351 - 2373
      Abstract: Temporal registration of sensors is an essential preprocessing step in multisensor target tracking systems. A new approach for multisensor time-offset estimation is proposed in this article. First, the time offset pseudomeasurement equation is derived and calculated in both centralized and decentralized scenarios, where measurements and local tracks are available at the fusion center, respectively. The observability of time offset is analyzed theoretically, which shows that only relative time offsets between sensors are observable. Second, a two-sensor two-stage filtering method is developed with four different formulations corresponding to different time-offset statistical models and target dynamic models to obtain a relative time-offset estimate. A multisensor two-stage filter is also proposed to obtain a minimum-bias time-offset estimate. Furthermore, the interacting multiple model estimator is used to deal with temporal registration in the presence of target maneuvers. Finally, the posterior Cramér–Rao lower bound (PCRLB) is derived for relative time-offset estimation. Simulation results show that the proposed algorithm with two sensors yields an empirically unbiased estimate of the relative time offset, and that the root-mean-square errors (RMSEs) match the corresponding PCRLB. Simulation results for multisensor target tracking are also presented to demonstrate the validity of the proposed algorithms.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Accurate Homing of Parafoil Delivery Systems Based Glide-Ratio Control
    • Authors: Hao Sun;Qinglin Sun;Xianyi Zeng;Shuzhen Luo;Wannan Wu;Zengqiang Chen;
      Pages: 2374 - 2389
      Abstract: In this article, the proposed method first evaluates the effects on aerodynamic force caused by flight velocity and angular velocity of the parafoil delivery system and performs an active disturbance rejection control in the horizontal direction. Moreover, a glide-ratio controller is designed based on the characteristics of the symmetrical flap deflection. For resisting its disturbance, a feedforward compensation unit is designed with the glide-ratio controller. The performance is effectively validated through hardware-in-the-loop simulation.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Gaussian Conditionally Markov Sequences: Algebraically Equivalent Dynamic
           Models
    • Authors: Reza Rezaie;X. Rong Li;
      Pages: 2390 - 2405
      Abstract: The conditionally Markov (CM) sequence contains different classes, including Markov, reciprocal, and so-called $text{CM}_L$ and $text{CM}_F$ (two CM classes defined in our previous work). Markov sequences are special reciprocal sequences, and reciprocal sequences are special $text{CM}_L$ and $text{CM}_F$ sequences. Each class has its own forward and backward dynamic models. The evolution of a CM sequence can be described by different models. For a given problem, a model in a specific form is desired or needed, or one model can be easier to apply and better than another. Therefore, it is important to study the relationship between different models and to obtain one model from another. This article studies this topic for models of nonsingular Gaussian $text{CM}_L$, $text{CM}_F$, reciprocal, and Markov sequences. Two models are probabilistically equivalent (PE) if their stochastic sequences have the same distribution and are algebraically equivalent (AE) if their stochastic sequences are pathwise identical. A unified approach is presented to obtain an AE forward/backward $text{CM}_L$/$text{CM}_F$/reciprocal/Markov model from another such model. As a special case, a backward Markov model AE to a forward Markov model is obtained. While existing results are restricted to models with nonsingular state transition matrices, our approach is not. In addition, a simple approach -s presented for studying and determining Markov models, whose sequences share the same reciprocal/$text{CM}_L$ model.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Trajectory Optimization for High-Altitude Long-Endurance UAV Maritime
           Radar Surveillance
    • Authors: Angus Brown;David Anderson;
      Pages: 2406 - 2421
      Abstract: For an unmanned aerial vehicle (UAV) carrying out a maritime radar surveillance mission, there is a tradeoff between maximizing information obtained from the search area and minimizing fuel consumption. This article presents an approach for the optimization of a UAV's trajectory for maritime radar wide area persistent surveillance to simultaneously minimize fuel consumption, maximize mean probability of detection, and minimize mean revisit time. Quintic polynomials are used to generate UAV trajectories due to their ability to provide complete and complex solutions while requiring few inputs. Furthermore, the UAV dynamics and surveillance mission requirements are used to ensure that a trajectory is realistic and mission compatible. A wide area search radar model is used within this article in conjunction with a discretized grid in order to determine the search area's mean probability of detection and mean revisit time. The trajectory generation method is then used in conjunction with a multiobjective particle swarm optimization algorithm to obtain a global optimum in terms of path, airspeed (and thus time), and altitude. The performance of the approach is then tested over two common maritime surveillance scenarios and compared to an industry recommended baseline.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Fast Detection of Distant, Infrared Targets in a Single Image Using
           Multiorder Directional Derivatives
    • Authors: Yanguang Bi;Junzhang Chen;Heng Sun;Xiangzhi Bai;
      Pages: 2422 - 2436
      Abstract: The fast and robust detection of far targets is one of the key techniques in infrared searching and tracking applications. Using multiorder directional derivatives, an effective and concise detection method performed on a single IR image is proposed in this article. First, multiorder directional derivatives of an image are derived from the facet model. According to the derivative characteristics of small targets, enhancement filters are designed to maximize the target components. Convolved with these filters, the small targets are enhanced and the backgrounds are suppressed in each derivative subband. The final result is obtained by fusing all these filtered derivative subbands. The experimental results demonstrate that the proposed method consistently achieves a robust and effective performance on all datasets. In addition, the low computational complexity makes the proposed method suitable for real time detection purpose.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • PCRB and IMM for Target Tracking in the Presence of Specular Multipath
    • Authors: Marcel Hernandez;Alfonso Farina;
      Pages: 2437 - 2449
      Abstract: This article considers the general problem of tracking a noncooperative target in the presence of specular multipath. We revisit a novel posterior Cramér–Rao bound (PCRB) methodology for this problem [1] and develop a robust interacting multiple model (IMM) extended Kalman filter (EKF) implementation. Both the PCRB and the IMM-EKF augment the target state to include the multipath parameters. The approaches are demonstrated via a simulated scenario, in which an airborne radar tracks a low-altitude airborne target. It is shown that the PCRB increases rapidly subsequent to the multipath effect occurring, indicating that tracking performance is significantly degraded at such times. Furthermore, it is shown that the IMM-EKF offers near-optimal performance, with target state estimation errors consistently within 15% of the PCRB. The IMM-EKF also consistently provides credible estimates. It is concluded that the PCRB methodology and the IMM-EKF tracker provide powerful tools for performance assessment and target state estimation in challenging multipath scenarios.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Robust Earth Observation Satellite Scheduling With Uncertainty of Cloud
           Coverage
    • Authors: Xinwei Wang;Guopeng Song;Roel Leus;Chao Han;
      Pages: 2450 - 2461
      Abstract: Earth observation satellites (EOSs) are specially equipped with remote sensing instruments to acquire images. In practical EOS scheduling, the uncertainty of cloud coverage is inevitable. We are the first to address robust EOS scheduling under uncertainty due to cloud coverage where the objective function aims to maximize the entire observation profit. We provide a robust formulation of the scheduling problem on the basis of a budgeted uncertainty set, while preserving the formulation linearity. A column-generation-based heuristic is also developed, in which the scheduling decisions in each satellite orbit are represented as columns. Eventually, a high-quality feasible solution is obtained using the generated columns. Extensive simulations are conducted on the basis of one of China's EOS constellations. The results indicate that the average optimality gap is less than 5%, which validates the performance of the proposed heuristic.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • A Frequency Diversity Algorithm for Extending the Radar Doppler Velocity
           Nyquist Interval
    • Authors: Vijay Venkatesh;Lihua Li;Matthew McLinden;Michael Coon;Gerald M. Heymsfield;Simone Tanelli;Hayk Hovhannisyan;
      Pages: 2462 - 2470
      Abstract: Compact millimeter wavelength radars have been widely used for applications such as remote sensing of clouds, guidance avionics, and recently, automotive navigation. However, the short wavelength of these radars limits their maximum unambiguous Doppler velocity. A common solution to this problem is to subsequently unfold the Doppler velocity estimate with the staggered pulse repetition time (PRT) algorithm, which requires two different PRTs to be employed in sequence. This article investigates a potentially more rapid method to extend the Doppler velocity Nyquist interval. We estimate Doppler velocity using a pair of frequency diverse pulses separated by a time lag that is significantly shorter than the PRT. During the first PRT, two pulses with center frequencies $f_1$, followed by $f_2$, separated by a lag $tau$ are transmitted. During the next PRT, the pulses transmitted are in the order $f_2$ followed by $f_1$. Doppler velocity is then estimated using the sum of the Doppler phases derived from $f_1$/$f_2$ and $f_2$/$f_1$ sequences. The focus of this article is the demonstration of this algorithm in a beam-filled scenario and the error canceling algorithm design. Based on Monte-Carlo simulations and data collected with the NASA Goddard Space Flight center's Cloud Radar System, the algorithm is demonstrated on nearly static surface echoes. Projected aircraft speeds and traditional pulse-pair estimates are employed as references. The algorithm was found to perform adequately on surface echoes for a low spectrum width of the order of 0.5 m/s and SNR comparable to 20 dB. Doppler velocity retrievals in a cirrus cloud layer with low velocity turbulence retained some qualitative structure, albeit with significantly degraded precision due to the lost coherence.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Efficient Weighted Centroid Technique for Crowdsourcing GNSS RFI
           Localization Using Differential RSS
    • Authors: Pai Wang;Yu T. Morton;
      Pages: 2471 - 2477
      Abstract: Radio frequency interference (RFI) localization is important for ensuring the accuracy and integrity of global navigation satellite system receivers in numerous applications. In this letter, an efficient RFI localization technique is presented based on differential received signal strength (DRSS) measurements from crowdsourcing devices. A DRSS weighting scheme allocates weights to the position solutions of the receivers that detect the RFI. The weighted centroid of the receiver positions generates the RFI location. The method presented in this letter can also provide an initial estimation for the conventional iterative localization approach to improve localization accuracy and convergence speed. Simulation results are presented to demonstrate the effectiveness of the proposed method being used independently or integrated with the iterative method.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • A Fast Labeled Multi-Bernoulli Filter Using Belief Propagation
    • Authors: Thomas Kropfreiter;Florian Meyer;Franz Hlawatsch;
      Pages: 2478 - 2488
      Abstract: We propose a fast labeled multi-Bernoulli (LMB) filter that uses belief propagation for probabilistic data association. The complexity of our filter scales only linearly in the numbers of Bernoulli components and measurements, while the performance is comparable to or better than that of the Gibbs sampler-based LMB filter.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Unimodular Waveform Design With Desired Ambiguity Function for Cognitive
           Radar
    • Authors: Hamid Esmaeili-Najafabadi;Henry Leung;Peter W. Moo;
      Pages: 2489 - 2496
      Abstract: In this correspondence, we target the problem of radar waveform design based on the ambiguity function. The problem is formulated as an optimization, where the nonconvex unimodularity constraint is also considered. The problem is solved by successive application of majorization minimization (MM) and projected gradient descent algorithm (PGD). The proposed method has the unprecedented ability to synthesize nonzero subregions. The superiority of the proposed algorithm in achieving zero subregions is confirmed through simulation, where a suppression superiority of at least 6 dB is evident compared to the best state-of-the-art benchmark.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • Adaptive Bit Loading With Reduced Computational Time and Complexity for
           Multicarrier Wireless Communications
    • Authors: Youssef Iraqi;Arafat Al-Dweik;
      Pages: 2497 - 2506
      Abstract: This correspondence presents an efficient bit loading technique that enables reduction of the time and computational complexity requirements for mobile wireless multicarrier communications, while satisfying certain bit-error-rate constraints. The complexity reduction is achieved by exploiting the channel correlation to reduce the number of subcarriers involved in the bit loading process, and consequently, the required computational time is reduced significantly. The computational complexity of the bit allocation process can be designed to match the system computational capabilities by deriving a theoretical upper bound on the average number of subcarriers involved in the bit loading process. The obtained results demonstrate that the proposed bit loading process time complexity is only 14% of conventional techniques at the signal-to-noise ratio of 20 dB with a throughput loss of about 13%.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
  • On the Effects of Channel Sparsity on Joint Estimators in Aeronautical
           Telemetry
    • Authors: Md. Shah Afran;Mohammad Saquib;Michael Rice;
      Pages: 2507 - 2514
      Abstract: Minimum mean-squared error (MMSE) equalizers are a viable solution to mitigate the frequency selectivity of the aeronautical telemetry channel. Because the MMSE equalizer filter coefficients are a function of the carrier frequency offset (CFO), the equivalent discrete-time channel, and the noise variance, reliable estimates of those parameters are required. The CFO is due primarily to the high velocity of the airborne transmitter. Because the equivalent discrete-time channel in aeronautical telemetry is sparse, the performance of the joint estimator based on a sparse channel estimator is superior to the performance of a traditional nonsparse maximum-likelihood-inspired joint estimator. The improvement is seen in lower estimator error variances for the parameters, particularly for the CFO and channel estimate, and in the postequalizer bit-error rate. Simulation results demonstrate that the postequalizer bit-error rate using the sparse estimator is almost as good as that using ideal estimators.
      PubDate: June 2020
      Issue No: Vol. 56, No. 3 (2020)
       
 
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