Article
Engineering, Electrical & Electronic
Fangqing Wen, Junpeng Shi, Zijing Zhang
Summary: This paper revisits the problem of multiple parameters estimation for coherent targets in bistatic EMVS-MIMO radar. Three generalized spatial smoothing estimators are proposed, which are capable of providing polarization information of the coherent targets without sacrificing it. These estimators do not require any constrain on the geometries of the Tx/Rx EMVS arrays and are computationally friendly yet retain robustness to the sensor position error.
Article
Engineering, Electrical & Electronic
Xiangyang Wang, Xiaolu Lv, Rui Wang
Summary: In this paper, a novel geometric algebra (GA)-based localization method is proposed for direction of arrival (DOA), range, and polarization estimation of near-field (NF) non-circular (NC) sources for a symmetric MIMO array. The proposed method converts the output of an electromagnetic vector sensor (EMVS) into a multi-vector through a GA matrix transformation, and then estimates the DOA and range parameters based on the GA-based NC rank reduction (GANC-RARE) algorithm. The polarization can be estimated based on the modified GA-based NC multiple signal classification (MGANC-MUSIC) algorithm using the estimated DOAs and ranges. The computational complexity analysis demonstrates the improvement in memory spaces and computation efforts compared to traditional methods.
DIGITAL SIGNAL PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Srinivasarao Chintagunta
Summary: This letter presents an approach for estimating the joint two-dimensional direction of arrival (DOA) of coherent targets in monostatic MIMO radar using EV sensors. The approach can resolve coherent targets without any preprocessing and locate multiple targets with identical azimuth/elevation angles, and also automatically pair the 2D directional angles and polarization angles. The presented approach shows improved estimation performance compared to existing state-of-the-art methods, as verified by simulation results.
Article
Computer Science, Information Systems
Giorgio Guerzoni, Elahe Faghand, Giorgio Matteo Vitetta, Loris Vincenzi, Esfandiar Mehrshahi
Summary: This paper proposes two novel calibration methods for radar devices, which simplify the calibration process and improve the accuracy of target parameter estimation.
Article
Engineering, Electrical & Electronic
Xianpeng Wang, Mengxing Huang, Liangtian Wan
Summary: This paper addresses the issue of two-dimensional direction-of-departure and direction-of-arrival estimation for bistatic MIMO radar with coprime EMVS, proposing a tensor-based subspace algorithm. By utilizing the tensor nature of array measurements and the uniformity of coprime EMVS-MIMO radar, the algorithm achieves accurate signal and angle estimation. The proposed method outperforms current state-of-the-art algorithms in terms of estimation performance, as validated through computer simulations.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Geochemistry & Geophysics
Sizhe Gao, Hui Ma, Hongwei Liu, Yang Yang
Summary: In this article, we propose an efficient direction of departure (DOD) and direction of arrival (DOA) estimation method for bistatic multiple-input multiple-output (MIMO) radar with faulty arrays. A third-order tensor model is built to better utilize the measurement 3-D structure. The proposed algorithm exploits the multidimensional structure of the signal without estimating the signal subspace and shows improved robustness and resolving correlated targets compared to traditional matrix completion (MC) methods.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Engineering, Aerospace
Fangqing Wen, Junpeng Shi, Jin He, Trieu-Kien Truong
Summary: This article proposes an L-shaped sparse array topology for a bistatic EMVS-MIMO radar, which has a larger interelement distance than half-wavelength. A fast algorithm is proposed to estimate the 2D-DOD and 2D-DOA using direction cosine estimates obtained from the sparse subarrays' rotational invariance properties and vector cross-product of normalized Poynting vectors. The proposed framework achieves better estimation accuracy than existing methods and is more flexible.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Environmental Sciences
Yongwei Zhang, Yongchao Zhang, Jiawei Luo, Yulin Huang, Jianan Yan, Yin Zhang, Jianyu Yang
Summary: This paper proposes a method by achieving an equivalent transformation and decomposes the optimization problem into three subproblems based on ADMM to reduce computational complexity.
Article
Engineering, Electrical & Electronic
Chao-Yi Wu, Tianyi Zhang, Jian Li, Tan F. Wong
Summary: This paper investigates the problem of target parameter estimation in phase modulated continuous wave multiple-input multiple-output radar systems with quantized observations. The Cramer-Rao bound is derived for jointly estimating targets' amplitudes, time delays, Doppler shifts, and directions, providing an efficient method to analyze estimation performance achieved by different quantization schemes. The maximum likelihood estimator and a direct grid-based method are devised to obtain the ML estimates, and a two-stage scheme is proposed to improve efficiency. Simulation results demonstrate that the proposed scheme approaches the CRB and that using quantized observations does not significantly affect estimation performance when targets' amplitudes are similar.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Takayuki Kitamura, Kei Suwa
Summary: This article introduces a novel multiple-input-multiple-output synthetic aperture radar imaging algorithm, which can be applied to security checkpoints attached to a moving walkway. The algorithm features transmitting-signal multiplexing on the Doppler frequency domain, reducing data acquisition time and achieving image reconstruction of dangerous objects.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2022)
Article
Engineering, Electrical & Electronic
Chang-Xin Cai, Guan-Jun Huang, Fang-Qing Wen, Xin-Hai Wang, Lin Wang
Summary: This paper addresses the issue of 2D-DOA estimation for EMVS arrays in the presence of nonuniform noise and proposes an improved subspace-based algorithm. By recasting the nonuniform noise problem as a matrix completion problem, the noiseless array covariance matrix is recovered through convex optimization. The proposed algorithm leverages the shift invariant principle and normalized polarization steering vector of EMVS arrays to estimate 2D-DOA and polarization angles effectively.
INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION
(2021)
Article
Engineering, Aerospace
Pasquale Di Viesti, Alessandro Davoli, Giorgio Guerzoni, Giorgio M. M. Vitetta
Summary: In this article, two recursive algorithms based on a maximum likelihood approach are introduced for detecting multiple superimposed tones in noise and estimating their parameters. These algorithms combine a novel single-tone estimator with a sequential cancellation procedure and provide a more accurate and efficient solution compared to other techniques in the presence of multiple closely spaced tones. Additionally, they can be used for target detection and spatial coordinate estimation in multiple-input multiple-output frequency-modulated continuous wave radar systems.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
David Werbunat, Benedikt Meinecke, Benedikt Schweizer, Juergen Hasch, Christian Waldschmidt
Summary: This article introduces a network concept consisting of an orthogonal frequency-division multiplexing (OFDM) radar and repeater elements, which ensures signal coherency by retransmitting reflections back to the radar. A new method for coherent angle estimation and analysis on the radar is proposed, showing promising results in measurements at 77 GHz.
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES
(2021)
Article
Engineering, Electrical & Electronic
Jinli Chen, Shanteng Fu, Xicheng Zhu, Jiaqiang Li
Summary: This study proposes an improved tensor completion method for handling sensor failures in MIMO radar to achieve more accurate data recovery in direction-of-arrival (DOA) estimation. By introducing tensor truncated convolution nuclear norm minimization (CNNM) and alternating direction method of multipliers (ADMM), the proposed method effectively completes tensors with structurally missing entries, leading to superior performance in MIMO radar.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Aerospace
Maozhong Fu, Chunxian Gao, Yuhan Li, Zhenmiao Deng, Daqing Chen
Summary: A new angle estimation approach is proposed to solve the target resolution problem in amplitude comparison monopulse systems when multiple targets occupy the same range-azimuth cell by modeling the signal in the frequency domain. The closely spaced targets in the same range-azimuth cell can be well resolved through joint maximum likelihood estimation, utilizing the monopulse ratio technique for angle estimates.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Alam Abbas Syed, Hassan Foroosh
Summary: This paper presents effective methods using spherical polar Fourier transform data for two different applications: 3D volumetric registration and machine learning classification network. The proposed method for registration offers unique and effective techniques, handling arbitrary large rotation angles and showing robustness. The modified classification network achieves robust classification results in processing spherical data.
Article
Engineering, Electrical & Electronic
Ruibo Fan, Mingli Jing, Jingang Shi, Lan Li, Zizhao Wang
Summary: In this study, a new low-rank sparse decomposition algorithm named TVRPCA+ is proposed for foreground-background separation. The algorithm combines spectral norm, structured sparse norm, and total variation regularization to suppress noise and obtain cleaner foregrounds. Experimental results demonstrate that TVRPCA+ achieves high performance in complex backgrounds and noise scenarios.
Article
Engineering, Electrical & Electronic
Omair Aldimashki, Ahmet Serbes
Summary: This paper proposes a coarse-to-fine FrFT-based algorithm for chirp-rate estimation of multi-component LFM signals, which achieves improved performance and a reduced signal-to-noise breakdown threshold by utilizing mathematical models for coarse estimation and a refined estimate-and-subtract strategy. Extensive simulation results demonstrate that the proposed algorithm performs very close to the Cramer-Rao lower bound, with the advantages of eliminating leakage effect, avoiding error propagation, and maintaining acceptable computational cost compared to other state-of-the-art methods.
Article
Engineering, Electrical & Electronic
Xinlei Shi, Xiaofei Zhang, Yuxin Sun, Yang Qian, Jinke Cao
Summary: In this paper, a low-complexity localization approach for multiple sources using two-dimensional discrete Fourier transform (2D-DFT) is proposed. The method computes the cross-covariance and utilizes phase offset method and total least square solution to obtain accurate position estimates.
Article
Engineering, Electrical & Electronic
Prabhanjan Mannari, Ratnasingham Tharmarasa, Thiagalingam Kirubarajan
Summary: This paper discusses the problem of extended target tracking for a single 2D extended target with a known convex polytope shape and dynamics. It proposes a framework based on the existing point multitarget tracking framework to address the challenges of uncertainty in shape and kinematics, as well as self-occlusion. The algorithm developed using this framework is capable of dynamically changing the number of parameters used to describe the shape and estimating the whole target shape even when different parts of the target are visible at different frames.
Article
Engineering, Electrical & Electronic
Yongsong Li, Zhengzhou Li, Jie Li, Junchao Yang, Abubakar Siddique
Summary: This paper proposes a weighted adaptive ring top-hat transformation (WARTH) for extracting infrared small targets in complex backgrounds. The WARTH method effectively measures local and global feature information using an adaptive ring-shaped structural element and a target awareness indicator, resulting in accurate detection of small targets with minimized false alarms.
Article
Engineering, Electrical & Electronic
Yu Wang, Zhen Qin, Jun Tao, Yili Xia
Summary: In this paper, an enhanced sparsity-aware recursive least squares (RLS) algorithm is proposed, which combines the proportionate updating (PU) and zero-attracting (ZA) mechanisms, and introduces a general convex regularization (CR) function and variable step-size (VSS) technique to improve performance.
Article
Engineering, Electrical & Electronic
Neil J. Bershad, Jose C. M. Bermudez
Summary: This paper analyzes the impact of processing delay on the Least Mean Squares (LMS) algorithm in system identification, highlighting bias issues in the resulting weight vector.
Article
Engineering, Electrical & Electronic
Kanghui Jiang, Defu Jiang, Mingxing Fu, Yan Han, Song Wang, Chao Zhang, Jingyu Shi
Summary: In this paper, a novel method for velocity estimation using multicarrier signals in a single dwell is proposed, which effectively addresses the issue of Doppler ambiguity in pulse Doppler radars.
Article
Engineering, Electrical & Electronic
Xiao-Jun Zhang, Peng-Lang Shui, Yu-Fan Xue
Summary: This paper proposes a method for low-velocity small target detection in maritime surveillance radars. It models sea clutter sequences using the spherical invariant random vector (SIRV) model with block tridiagonal speckle covariance matrix and inverse Gamma distributed texture. The proposed detector, which is a long-time adaptive generalized likelihood ratio test with linear threshold detector (GLRT-LTD), shows competitive detection performance in experiments.
Article
Engineering, Electrical & Electronic
Aiyi Zhang, Fulai Liu, Ruiyan Du
Summary: This paper proposes an adaptive weighted robust data recovery method with total variation regularization for hyperspectral image. The method models the HSI recovery problem as a tensor robust principal component analysis optimization problem, decomposing the data into low-rank HSI data, outliers, and noise component. An adaptive weighted strategy is then defined to impose on the tensor nuclear norm and outliers, using the priori information of singular values and strengthening the sparsity of outliers.
Article
Engineering, Electrical & Electronic
Hamid Asadi, Babak Seyfe
Summary: This paper presents a novel approach for estimating the model order in the presence of observation errors. The proposed method is based on correntropy estimation of eigenvalues in the observation space, which is further enhanced by resampling the observations using the bootstrap method. The algorithm partitions the observation space into signal and noise subspaces using the covariance matrix of mixtures, and determines the model order based on a correntropy estimator with kernel functions. Theoretical analysis and comparative evaluations demonstrate the superiority of this information-theoretic approach.
Article
Engineering, Electrical & Electronic
Buket colak Guvenc, Engin Cemal Menguc
Summary: In this paper, a novel family of online censoring based complex-valued least mean kurtosis (CLMK) algorithms is proposed. The algorithms censor less informative complex-valued data streams and reduce the costs of data processing without affecting accuracy. Robust algorithms are also developed to handle outliers. The simulation results confirm the attractive features of the proposed algorithms in large-scale system identification and regression scenarios.
Article
Engineering, Electrical & Electronic
Yun Su, Weixian Tan, Yifan Dong, Wei Xu, Pingping Huang, Jianxin Zhang, Diankun Zhang
Summary: In this study, a novel method for detecting low-resolution and small targets in millimeter wave radar images is proposed. The Wavelet-Conv structure and Wavelet-Attention mechanism are introduced to overcome the limitations of existing detectors. Experimental results demonstrate that the proposed method improves recall and mean average precision while maintaining competitive inference speed.
Article
Engineering, Electrical & Electronic
Xin Wang, Xingxing Jiang, Qiuyu Song, Jie Liu, Jianfeng Guo, Zhongkui Zhu
Summary: This study proposes a variational mode extraction (VME) method for extracting specific modes from complicated signals. By exploring the convergence property of VME, strategies for identifying ICF and determining the balance parameter are designed, and a bandwidth estimation strategy is constructed. The effectiveness of the proposed method for bearings fault diagnosis is verified and compared with other methods.