Article
Engineering, Electrical & Electronic
Fangqing Wen, Junpeng Shi, Zijing Zhang
Summary: This paper proposes a novel subspace algorithm for target localization in bistatic MIMO radar system, which can automatically provide paired 2D-DOD, 2D-DOA, and polarization parameters estimation, and is insensitive to sensor position error. The algorithm is detailed analyzed and numerical simulations are provided to verify its effectiveness.
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
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, 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
Computer Science, Information Systems
Bin Li, Shusen Wang, Zhiyong Feng, Jun Zhang, Xianbin Cao, Chenglin Zhao
Summary: This study addresses the issue of fast and accurate estimation of high-resolution pseudospectrum in massive MIMO radars by leveraging randomized matrix sketching techniques. The approximation of the large matrix product is achieved by the product of two small matrices abstracted via random sampling, and an additional algorithm is designed to refine the approximated results for exact pseudospectrum estimation.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Civil
Yuehao Guo, Xianpeng Wang, Xiang Lan, Ting Su
Summary: Intelligent Transportation System (ITS) is introduced to address the safety problems and economic losses caused by traffic accidents. The developed scheme incorporates frequency diversity array multiple-input multiple-output (FDA-MIMO) radar and tensor decomposition to improve the real-time performance of target location estimation. By constructing a four-dimensional tensor and using parallel factor (PARAFAC) decomposition to handle colored noise, as well as optimizing and using Lagrange multiplier to address array gain-phase error, this scheme can efficiently obtain the location information of motor vehicles.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Environmental Sciences
Lei Zhang, Han Wang, Fang-Qing Wen, Jun-Peng Shi
Summary: In this paper, the multiple parameter estimation problem for bistatic EMVS-MIMO radar with coherent targets is investigated. Three tensor-aware spatial smoothing estimators are introduced and analyzed in detail. Numerical experiments validate the theoretical findings.
Article
Engineering, Electrical & Electronic
Bin Li, Shusen Wang, Jun Zhang, Xianbin Cao, Chenglin Zhao
Summary: This study proposes two efficient methods for fast subspace computation and accurate angle of arrival estimation in radar systems. By utilizing random sampling and projection techniques, these methods significantly accelerate the estimation speed. Experimental results show that these methods are much faster and almost as accurate as traditional methods.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Xiaohuan Wu, Yaxin Liu, Xu Yang
Summary: This paper focuses on the direction finding in bistatic MIMO radar system with UPAs for target localization, using ANM and SDP to achieve a gridless model for full angle information of targets, and ADMM for reducing computational complexity. Simulation results demonstrate high estimation accuracy and low computational complexity.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Linga Reddy Cenkeramaddi, Prabhat Kumar Rai, Aveen Dayal, Jyoti Bhatia, Aarav Pandya, J. Soumya, Abhinav Kumar, Ajit Jha
Summary: This article presents a novel machine learning based angle estimation and field of view enhancement techniques for mmWave FMCW radars operating in the frequency range of 77 - 81 GHz. The orientation of antenna elements is utilized to enhance both azimuth and elevation FoV. With the proposed angle estimation technique, a RMSE of 2.56 degrees is achieved for rotating radars, making these techniques highly useful for applications such as ground station traffic monitoring and control systems.
IEEE SENSORS JOURNAL
(2021)
Article
Environmental Sciences
Sheng Chen, Yongbo Zhao, Yili Hu, Ben Niu
Summary: This paper discusses the issue of low-angle estimation in MIMO radar and proposes a BSC algorithm to improve the performance. The algorithm solves initial angle estimation and multipath coefficient estimation using beamspace data, reduces data dimensions, and provides closed-form solutions for three multipath scenes. The method achieves high estimation accuracy while requiring few processing resources and demonstrates superior computational complexity for engineering applications.
Article
Engineering, Electrical & Electronic
Mingjian Ren, Guoping Hu, Junpeng Shi, Hao Zhou
Summary: This paper proposes a tensor-based algorithm to suppress the performance degradation in nested bistatic multiple-input multiple-output radar caused by gain-phase error. The algorithm constructs a three-way tensor model using the distribution characteristics of gain-phase error and employs the position distribution of calibration and virtual sensors for error estimation. Experimental results demonstrate that the proposed algorithm exhibits superior performance.
Article
Engineering, Electrical & Electronic
Sohee Lim, Jaehoon Jung, Byeong-ho Lee, Jeongsik Choi, Seong-Cheol Kim
Summary: Automotive sensors are crucial for autonomous driving and accurately estimating vehicle orientation is essential for responding to unpredictable situations. This article proposes a method using a cascaded MIMO FMCW radar system to estimate vehicle orientation. By applying signal preprocessing and regression algorithms, the proposed method achieves accurate estimation of the orientation angle.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Zhennan Liang, Teng Ma, Shaoqiang Chang, Kaixiang Zhang, Haibo Liu, Quanhua Liu
Summary: Highly accurate target angle estimation is crucial for target tracking. When multiple targets are close to each other, their measurement points may be located in the same range-azimuth cell. This article proposes a closely spaced extended target angle estimation method that utilizes the principle of invariance of extended target scattering characteristics and maximum likelihood estimation to address the issue of multiple target scattering points falling within the same cell.
IEEE SENSORS JOURNAL
(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
Fangqing Wen, Junpeng Shi, Zijing Zhang
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2020)
Article
Engineering, Multidisciplinary
Yongqiang Yang, Ningjun Ruan, Guanjun Huang, Junpeng Shi, Fangqing Wen
Summary: A novel 2D DOD and DOA estimation algorithm for coprime MIMO radar is proposed in this paper, which does not require obtaining signal subspace by eigendecomposition. The algorithm demonstrates better estimation performance and simpler computation performance compared to state-of-the-art algorithms. Its effectiveness is verified through simulation results.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Computer Science, Information Systems
Tingping Zhang, Di Wan, Xinhai Wang, Fangqing Wen
Summary: This paper introduces a novel estimator that is suitable for EVS arrays with arbitrary geometry, insensitive to spatially colored noise, and has been verified for its effectiveness through numerical simulations.
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
(2021)
Article
Telecommunications
Jinlong Wu, Fangqing Wen, Junpeng Shi
Summary: This letter discusses angle estimation for sensors in a MIMO system corrupted by direction-dependent mutual coupling (MC) effect, and proposes an efficient algorithm. The algorithm releases the MC effect through selection matrices and utilizes rotational invariance techniques to obtain accurate angle estimation, which is much more efficient compared to current spectrum search methods.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Telecommunications
Jinlong Wu, Fangqing Wen, Junpeng Shi
Summary: This letter investigates target localization and sensor calibration in bistatic MIMO radar in the presence of direction-dependent mutual coupling, proposing a MUSIC-like methodology that links angle estimation to a quadratic optimization problem solved via Lagrange multiplier method. The proposed method is suitable for arbitrary sensor geometry, with numerical simulations validating its effectiveness.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Tingping Zhang, Di Wan, Xinhai Wang, Fangqing Wen
Summary: This paper generalizes the issue of angle estimation and mutual coupling self-calibration in a bistatic MIMO system with arbitrary sensor geometry. A MUSIC-like strategy is proposed to estimate DOD and DOA, and the mutual coupling coefficients are obtained by exploiting the orthogonality between signal and noise subspaces. The proposed method is suitable for arbitrary sensor geometry and is validated through simulation results.
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
(2021)
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
Computer Science, Information Systems
Fangqing Wen, Junpeng Shi, Guan Gui, Haris Gacanin, Octavia A. Dobre
Summary: This article proposes a novel framework for the three-dimensional (3-D) positioning of unmanned aerial vehicles (UAVs) using a bistatic multiple-input multiple-output (MIMO) radar to measure the two-dimensional (2-D) angle-of-departure (2D-AoD) and 2D-AoA. The proposed framework is computationally friendly and capable of positioning anonymous UAVs.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Fangqing Wen, Guan Gui, Haris Gacanin, Hikmet Sari
Summary: This paper proposes a compressive sampling framework for two-dimensional DOA and polarization estimation in mmWave polarized massive MIMO systems. The proposed approach reduces data volume through a reduced-dimension matrix and computes the signal subspace via eigendecomposition. It also utilizes rotational invariance characteristic to form a normalized polarization steering vector and applies the Poynting vector and least squares techniques for 2D-DOA and polarization estimation.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Zhe Zhang, Fangqing Wen, Junpeng Shi, Jin He, Trieu-Kien Truong
Summary: This letter proposes a method to estimate the 2-D direction-of-arrival (DOA) using a polarized uniform rectangular array (URA) under multipath propagation. The method establishes a parallel factor (PARAFAC) model that incorporates spatial response matrices, a polarization response matrix, and a source matrix. By taking the KhatriRao product with a full column rank factor matrix, the rank-deficiency of the source matrix is resolved, and three rearranged PARAFAC tensors are obtained. The estimation of 2D-DOA is then performed using the vector cross product-auxiliary rotational invariance technique (VCPARIT), which shows superiority over existing smoothing methods in terms of estimation accuracy.
IEEE SIGNAL PROCESSING LETTERS
(2023)
Article
Computer Science, Information Systems
Chong Shen, Fang Dong, Fangqing Wen, Ziheng Gong, Kun Zhang
Article
Computer Science, Information Systems
Chenxing Mao, Junpeng Shi, Fangqing Wen
Article
Computer Science, Information Systems
Tingting Liu, Fangqing Wen, Junpeng Shi, Ziheng Gong, Hui Xu
Article
Computer Science, Information Systems
Fangqing Wen, Zijing Zhang, Gong Zhang
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.
