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A reduced-dimension RML method for transmit beamspace-based MIMO radar

DIGITAL SIGNAL PROCESSING 2021年 114卷 103072-103072页

作者： Zhao, Yongbo Pang, Xiaojiao Chen, Sheng Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

In this paper, the problem of low angle estimation for multiple-input multiple-output (MIMO) radar is considered. Though the refined maximum likelihood (RML) algorithm can be directly applied to low angle estimation in MIMO radar, its computational burden is huge due to the large virtual aperture. Moreover, the conventional MIMO radar employs full waveform diversity, which actually sacrifices the emission gain. To reduce the computational burden and improve the transmit gain, a reduced-dimension RML method for transmit beamspace-based (TB-based) MIMO radar is developed. Firstly, the transmit beamspace (TB) matrix is designed to focus the transmit energy within the desired spatial sector. Then, to reduce the computational complexity and retain the estimation precision of the direct RML (D-RML) method for TB-based MIMO radar, a transmit-receive separate RML (TRS-RML) method is developed by applying the RML algorithm to the transmit and receive side respectively. Moreover, we propose to fuse the estimation results of the transmit and receive side together to improve the estimation precision. Theoretical analysis shows the TRS-RML method requires much lower computational burden than D-RML method. Numerical experiments show the proposed method has higher estimation accuracy compared with the D-RML method for the conventional MIMO radar in most angle region. (C) 2021 Elsevier Inc. All rights reserved.

关键词： multiple-input multiple-output radar Low angle estimation Refined maximum likelihood algorithm Multipath effect Transmit beamspace

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Closed-form estimation algorithm for EMVS-MIMO radar with arbitrary sensor geometry

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SIGNAL PROCESSING 2021年 186卷 108117-108117页

作者： Wen, Fangqing Shi, Junpeng Zhang, Zijing China Three Gorges Univ Coll Comp & Informat Technol Yichang 443002 Peoples R China Natl Univ Def Technol Coll Elect Countermeasure Hefei 230037 Peoples R China Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

In this paper, we investigate into the problem of target localization in bistatic MIMO radar system with the prototype of arbitrary EMVS. A novel subspace algorithm is derived, which offers closed-form solution to 2D-DOD and 2D-DOA estimation. The core of the proposed algorithm is to construct the normalized Poynting vector via the vector cross-product of two special vectors, which consist of the rotation invariant factors of the array and can be estimated through the least squares technique. The proposed algorithm can provide automatically paired 2D-DOD, 2D-DOA, and polarization parameters estimation. Moreover, it is insensitive to the sensor position error. The proposed algorithm is analyzed in detail, and numerical simulations are provided to verify its effectiveness. (C) 2021 Elsevier B.V. All rights reserved.

关键词： multiple-input multiple-output radar Electromagnetic vector sensors Angle estimation

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An Improved Propagator Estimator for DOA Estimation in Monostatic MIMO radar in the Presence of Imperfect Waveforms

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IEEE ACCESS 2019年 7卷 148771-148778页

作者： Shen, Chong Dong, Fang Wen, Fangqing Gong, Ziheng Zhang, Kun Hainan Univ State Key Lab Marine Resource Utilizat South Chin Haikou 570228 Hainan Peoples R China Yangtze Univ Natl Demonstrat Ctr Expt Elect & Elect Educ Jingzhou 434023 Peoples R China Beijing Univ Posts & Telecommun Telecommun Engn Management Beijing 100876 Peoples R China Hainan Trop Ocean Univ Educ Ctr MTA Sanya 572022 Peoples R China

This paper discusses the direction-of-arrival (DOA) estimation problem in multiple-input multiple-output (MIMO) radar with non-orthogonal waveforms. Unlike the traditional orthogonal waveforms-based counterparts, spatially colored noise as well as corrupted virtual direction matrix would appear due to the correlated waveforms in DOA estimation. To tackle these issues, an improved propagator estimator is developed. The spatially colored noise caused by waveform imperfectly is eliminated via cross-correlation technique. Thereafter, DOA is obtained by exploiting the propagator and invariant techniques. The proposed estimator does not involve eigendecomposition of the high dimensional matrix, and it provides closed-form solution for DOA estimation. Compared with the existing frameworks, it is computationally much more economic. Moreover, it offers very close DOA estimation accuracy to the matrix-based methods. Numerical simulations are carried out to show the improvement of the proposed estimator.

关键词： Direction-of-arrival estimation multiple-input multiple-output radar non-orthogonal waveforms propagator

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Target Localization in Bistatic EMVS-MIMO radar Using Tensor Subspace Method

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IEEE ACCESS 2019年 7卷 163119-163127页

作者： Mao, Chenxing Shi, Junpeng Wen, Fangqing Yangtze Univ Elect & Informat Sch Jingzhou 434023 Peoples R China Yangtze Univ Natl Demonstrat Ctr Expt Elect & Elect Educ Jingzhou 434023 Peoples R China Natl Univ Def Technol Hefei 230037 Peoples R China

Target localization is a fundamental task of multiple-input multiple-output (MIMO) radar systems with numerous applications. In this paper, we investigate into the localization problem in a bistatic MIMO radar with electromagnetic vector sensors (EMVS). Unlike the traditional scaler sensors, an EMVS is able to offer two dimensional (2D) direction finding, and it can provide additional polarization characteristics of the source. Therefore, target localization in bistatic EMVS-MIMO radar system involves 2D direction-of-departure (2D-DOD) and 2D direction-of-arrival (2D-DOA) estimation. Besides, we can obtain transmit polarization characteristics as well as polarization characteristics of the targets. To exploit the tensor nature of the array measurement after matched filters, a tensor subspace algorithm is developed, which estimates the target parameters via cross-product technique from tensor subspace. The proposed algorithm, which obtains closed-form solutions for parameters estimation, shows more accurate performance than the existing algorithm. Numerical simulations verify the effectiveness and improvement of the proposed algorithm.

关键词： multiple-input multiple-output radar electromagnetic vector sensors higher order singular value decomposition analysis estimation

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Computationally efficient DOD and DOA estimation for bistatic MIMO radar with propagator method

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INTERNATIONAL JOURNAL OF ELECTRONICS 2012年第9期99卷 1207-1221页

作者： Zhang, Xiaofei Wu, Hailang Li, Jianfeng Xu, Dazhuan Nanjing Univ Aeronaut & Astronaut Dept Elect Engn Nanjing 210016 Peoples R China

In this article, we consider a computationally efficient direction of departure and direction of arrival estimation problem for a bistatic multiple-input multiple-output (MIMO) radar. The computational loads of the propagator method (PM) can be significantly smaller since the PM does not require any eigenvalue decomposition of the cross correlation matrix and singular value decomposition of the received data. An improved PM algorithm is proposed to obtain automatically paired transmit and receive angle estimations in the MIMO radar. The proposed algorithm has very close angle estimation performance to conventional PM, which has a much higher complexity than our algorithm. For high signal-to-noise ratio, the proposed algorithm has very close angle estimation to estimation of signal parameters via rotational invariance technique algorithm. The variance of the estimation error and Cramer-Rao bound of angle estimation are derived. Simulation results verify the usefulness of our algorithm.

关键词： angle estimation multiple-input multiple-output radar propagator method

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Frequency Increment Design Method of MR-FDA-MIMO radar for Interference Suppression

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REMOTE SENSING 2023年第16期15卷 4070-4070页

作者： Wu, Zhixia Zhu, Shengqi Xu, Jingwei Lan, Lan Li, Ximin Zhang, Yiqun Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China

In the present complex electromagnetic environment, radar target detection is threatened by different kinds of interferences, especially mainlobe deceptive interference, which occupies the same energy distributions of targets spatially, meaning that targets and interferences cannot be discriminated. To make matters worse, the number of suppressible interferences is limited by the number of physical array elements, leading to the degradation of the suppression performance of traditional radar. In this work, we propose a frequency-increment-based interference suppression method for minimum redundancy frequency diverse array multiple-input multiple-output (MR-FDA-MIMO) radar, which effectively solves the aforementioned two problems. The interference suppression method consists of two steps: (i) in the sidelobe barrage interference suppression stage, the interference-plus-noise covariance matrix is reconstructed to overcome the influence of the true targets and mainlobe deceptive interference on the performance of the beamformer;(ii) in the mainlobe deceptive interference suppression stage, a nonadaptive beamforming method is employed to suppress mainlobe deceptive interference and overcome the impact of insufficient virtual samples on interference suppression performance. Additionally, we design a frequency-increment-based MR-FDA-MIMO radar, fully utilizing the advantages of the virtual array to enhance interference suppression performance and increase the number of interferences. Numerical experiments undertaken demonstrate the effectiveness of the algorithm under different scenarios.

关键词： frequency diverse array multiple-input multiple-output radar minimum redundancy array nonadaptive beamforming frequency increment

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Joint 2D-DOA estimation of coherent targets using EV sensors in MIMO radar

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SIGNAL PROCESSING 2022年 201卷

作者： Chintagunta, Srinivasarao IIIT Bhubaneswar Dept Etc Bhubaneswar 751003 Odisha India

This letter presents an approach for estimating the joint two-dimensional (2D) direction of arrival (DOA) of coherent targets in monostatic multiple-input and multiple-output (MIMO) radar using the electromagnetic vector (EV) sensors. The approach resolves coherent targets without any preprocessing and locates two or more targets having identical azimuth/elevation angles, and also automatically pairs the 2D directional (i.e., azimuth and elevation) angles and the 2D polarization angles. Compared with the existing state-of-the art methods, the presented approach shows improved estimation performance verified by the simulation results. (C) 2022 Elsevier B.V. All rights reserved.

关键词： Coherent targets Direction of arrival estimation Electromagnetic vector sensor multiple-input multiple-output radar

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An ADMM-qSPICE-Based Sparse DOA Estimation Method for MIMO radar

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REMOTE SENSING 2023年第2期15卷 446-446页

作者： Zhang, Yongwei Zhang, Yongchao Luo, Jiawei Huang, Yulin Yan, Jianan Zhang, Yin Yang, Jianyu Univ Elect Sci & Technol China UESTC Sch Informat & Commun Engn Chengdu 611731 Peoples R China Univ Elect Sci & Technol China UESTC Yangtze Delta Reg Inst Quzhou 324003 Peoples R China

In recent years, sparse direction-of-arrival (DOA) estimation for multiple-input multiple-output (MIMO) radar has attracted extensive attention and been extensively studied, especially the method based on the classic least absolute shrinkage and selection operator (LASSO) estimator. The alternating-direction method of multipliers (ADMM) is an effective method for solving this problem at the cost of introducing an additional user parameter. To avoid introducing an additional user parameter, this paper adopts an equivalent transformation in the form of the generalized SParse Iterative Covariance-based Estimation (qSPICE) cost function to obtain a mean squared minimized form of the cost function. Then, the problem is transformed into a sparse optimization problem in the form of a weighted LASSO. Next, this unconstrained optimization problem is decomposed into three subproblems, which are solved separately to reduce the dimension of each problem and thus reduce the overall computational complexity based on ADMM. Simulation results and measured data indicate that the proposed method significantly outperforms the traditional super-resolution DOA estimation method and ADMM-LASSO method and slightly outperforms qSPICE in terms of resolution and sidelobe suppression capability. In addition, the proposed method has a much lower computational complexity and substantially fewer iterations than qSPICE.

关键词： multiple-input multiple-output radar direction-of-arrival estimation sparse signal processing

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Generalized spatial smoothing in bistatic EMVS-MIMO radar

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SIGNAL PROCESSING 2022年 193卷 108406-108406页

This paper revisits the problem of multiple parameters estimation for coherent targets in bistatic EMVS-MIMO radar. By extending the spatial smoothing mechanism to the EMVS-MIMO radar, three generalized spatial smoothing estimators, named the TS approach, the RS approach and the TRS approach, have been proposed. The killer idea of the proposed methodologies is to recover the rank of the covariance matrix via averaging the array measurement in spatial domain, and then estimate the parameters from the coop-eration of the normalized vector cross-product technique and the LS method. Unlike the state-of-the-art polarization smoothing methods, the proposed methods would not sacrifice the polarization information, so that TS, RS and TRS are capable of providing polarization information of the coherent targets. The proposed estimators do not require any constrain on the geometries of the Tx/Rx EMVS arrays. They are computationally friendly yet retain robustness to the sensor position error. The proposed estimators are analyzed in detail, and numerical simulations are provided to verify their theoretical advantages.(c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://***/licenses/by-nc-nd/4.0/ )

关键词： multiple-input multiple-output radar Electromagnetic vector sensors Angle estimation Coherent targets

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MIMO radar Parallel Simulation System Based on CPU/GPU Architecture

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SENSORS 2022年第1期22卷 396-396页

作者： Liu, Gaogao Yang, Wenbo Li, Peng Qin, Guodong Cai, Jingjing Wang, Youming Wang, Shuai Yue, Ning Huang, Dongjie Xidian Univ Sch Elect Engn Xian 710071 Peoples R China

The data volume and computation task of MIMO radar is huge;a very high-speed computation is necessary for its real-time processing. In this paper, we mainly study the time division MIMO radar signal processing flow, propose an improved MIMO radar signal processing algorithm, raising the MIMO radar algorithm processing speed combined with the previous algorithms, and, on this basis, a parallel simulation system for the MIMO radar based on the CPU/GPU architecture is proposed. The outer layer of the framework is coarse-grained with OpenMP for acceleration on the CPU, and the inner layer of fine-grained data processing is accelerated on the GPU. Its performance is significantly faster than the serial computing equipment, and satisfactory acceleration effects have been achieved in the CPU/GPU architecture simulation. The experimental results show that the MIMO radar parallel simulation system with CPU/GPU architecture greatly improves the computing power of the CPU-based method. Compared with the serial sequential CPU method, GPU simulation achieves a speedup of 130 times. In addition, the MIMO radar signal processing parallel simulation system based on the CPU/GPU architecture has a performance improvement of 13%, compared to the GPU-only method.

关键词： graphics processing unit (GPU) central processing unit (CPU) parallel processing multiple-input multiple-output radar

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