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MIMO radar Parallel Simulation System Based on CPU/GPU Architecture

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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Joint DOA, range and polarization estimation based on geometric algebra for near-field non-circular source with a symmetric MIMO array

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DIGITAL SIGNAL PROCESSING 2023年第1期136卷

作者： Wang, Xiangyang Lv, Xiaolu Wang, Rui Shanghai Univ Sch Commun & Informat Engn Shanghai 200444 Peoples R China

multiple-input multiple-output (MIMO) radar is a new type of radar with excellent performance in target detection and parameter estimations. The MIMO radar equipped with electromagnetic vector sensors (EMVSs) can record multi-dimensional information of the electromagnetic (EM) signal. Traditional methods based on long vector model cannot preserve orthogonality between the outputs of each component of the EMVS and have high computational complexity. 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. First, the proposed method converts the output of an EMVS into a multi-vector through a GA matrix transformation. Then, the DOA and range parameters can be estimated by searching the one-dimensional (1-D) spectrum based on the GA-based NC rank reduction (GANC-RARE) algorithm. Finally, the polarization can be estimated by employing estimated DOAs and ranges based on the modified GA-based NC multiple signal classification (MGANC-MUSIC) algorithm. The computational complexity analysis demonstrates that our solution improves memory spaces of the covariance matrix and reduces computation efforts of the eigenvalue decomposition (EVD). The simulation results show the superiority and reliability of our proposed method in model error and coherent noise environment.(c) 2023 Elsevier Inc. All rights reserved.

关键词： multiple-input multiple-output radar Electromagnetic vector sensors Direction of arrival Geometric algebra Near-field Non-circular

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Robust low-range-sidelobe target synthesis for airborne FDMA-MIMO STAP radar

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IET radar SONAR AND NAVIGATION 2020年第10期14卷 1592-1602页

作者： Zhao, Yang Wu, Jianxin Suo, Zhiyong Liu, Xiaoyu Liang, Yi Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Sun Yat Sen Univ Sch Elect & Commun Engn Guangzhou 510275 Peoples R China

With the multi-function need for airborne space-time adaptive processing (STAP) radar, range synthesis is usually necessary for the follow-up function of target recognition. Utilising the excellent performance on orthogonality and bandwidth synthesis of the frequency division multiple access (FDMA) waveform and the longer accumulation time of multiple-input multiple-output (MIMO) radar, a robust low-sidelobe target synthesis method for airborne FDMA-MIMO STAP radar is developed. The spectra characteristics of target and clutter are first analysed. Then, the keystone transform is employed to mitigate velocity migration. To avoid gain fluctuation induced by multiple independent adaptive weight vectors, the robust STAP beamformer is developed. Finally, to decouple the range-angle coupling relationship resulted from the FDMA waveform, angle compensation is added in the robust STAP beamformer. Numerical examples are given to demonstrate the effectiveness of the presented method.

关键词： radar clutter space-time adaptive processing array signal processing airborne radar frequency division multiple access MIMO communication radar signal processing FDMA waveform range-angle coupling relationship robust STAP beamformer multiple independent adaptive weight vectors clutter low-sidelobe target synthesis method multiple-input multiple-output radar longer accumulation time frequency division multiple access waveform bandwidth synthesis orthogonality target recognition range synthesis airborne FDMA-MIMO STAP radar low-range-sidelobe target synthesis

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Spatial-temporal waveform design for MIMO radar without approximating the covariance matrix

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IET radar SONAR AND NAVIGATION 2020年第3期14卷 381-387页

作者： Zhang, Bo Dai, Fengzhou Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

In this study, a transmit waveform design method based on spatial-temporal optimisation for multiple-input multiple-output (MIMO) radar is proposed. The goal is not only to design the waveforms for beampattern matching, but also to minimise the autocorrelation sidelobes of the spatial synthesis signals of interested direction. Especially, to synthesise the constant envelope waveform directly, an improved sequential convex algorithm is proposed to tackle the non-convex problem in spatial optimisation. Then the autocorrelation sidelobes are reduced by using the steepest descent algorithm in temporal optimisation. Finally, the authors assess the effectiveness of the proposed technique through numerical simulations in comparison with the traditional and the alternating direction method of multipliers method.

关键词： concave programming waveform analysis MIMO radar optimisation radar antennas antenna arrays array signal processing covariance matrices gradient methods convex programming MIMO communication spatial-temporal waveform design MIMO radar covariance matrix transmit waveform design method spatial-temporal optimisation multiple-input multiple-output radar beampattern matching autocorrelation sidelobes spatial synthesis signals interested direction constant envelope waveform improved sequential convex algorithm nonconvex problem spatial optimisation steepest descent algorithm alternating direction method

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

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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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Study on Coding Scheme with EPC-MIMO radar in Clutter-Free Scenario 11

Study on Coding Scheme with EPC-MIMO Radar in Clutter-Free S...

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IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)

作者： Xu, Jingwei So, Hing Cheung Xidian Univ Xian 710071 Shaanxi Peoples R China City Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781728119465

In this paper, the element-pulse coding (EPC) based multiple-input multiple-output (MIMO) radar is studied for resolving range ambiguity in clutter-free scenario. The fundamental transmit and receive procedures as well as the relationship between encoding and decoding are presented. To address the range ambiguity issue, the EPC entries in element dimension are extended to be an arbitrary permutation of the Fourier basis entries. The beampattern is designed to extract the desired target signal while suppressing targets from nuisance range regions. Both conventional and enhanced array beamforming methods are discussed. Simulation examples are provided to demonstrate the effectiveness of the proposed method.

关键词： multiple-input multiple-output radar element-pulse coding range ambiguity Fourier basis array beamforming

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Fast Constant Modulus MIMO radar Waveform Design for Interference Mitigation

Fast Constant Modulus MIMO Radar Waveform Design for Interfe...

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IEEE radar Conference (radarConf)

作者： Zheng, Hao Jiu, Bo Liu, Hongwei Xidian Univ Natl Lab Radar Signal Proc Xian Peoples R China

ISBN: (纸本)9781728189420

In this paper, a fast constant modulus multiple-input multiple-output (MIMO) radar waveform design method is proposed for interference mitigation. In order to reduce the computational burden of optimizing waveform, a new transmit scheme is presented, which can decouple the spatial part and temporal part of the waveform design. Focusing on the spatial property of waveform, a novel cost function is proposed to minimize the maximum transmit power difference between interference region and target region. With the constant modulus constraint, the proposed cost function is intractable. To further improve the computational efficiency, a two-step strategy is proposed to obtain a suboptimal solution, which decomposes the original problem into a set of parallel beamformers design and a linear programming (LP) problem about the support time of beamformers. To optimize the beamformers efficiently, the majorization-minimization (MM) algorithm and its acceleration version are employed to tackle this problem. Numerical results show the efficiency of the proposed method.

关键词： Fast waveform design multiple-input multiple-output radar constant modulus transmit beampattern interference mitigation

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A sidelobe suppression algorithm for 77 GHz MIMO radars

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MEASUREMENT 2022年 190卷

作者： Yang, Lijie Xu, Tongkai Deng, Qingwen Zeng, Yuming Lu, Hao Li, Xiangdong Shen, Siyi Xu, Zhiwei Wang, Yueming Res Ctr Intelligent Sensing Syst Zhejiang Lab Hangzhou Peoples R China Zhejiang Univ Inst Marine Elect & Intelligent Syst Ocean Coll Zhoushan Peoples R China Chinese Acad Sci Shanghai Inst Tech Phys Key Lab Space Act Optoelect Technol Shanghai Peoples R China Univ Chinese Acad Sci Hangzhou Inst Adv Study Hangzhou Peoples R China

77 GHz radar has become a promising approach to enhance automotive safety by quickly detecting and identifying targets around the vehicle, especially in harsh weather conditions. This requires 77 GHz radars to provide environmental imaging with high resolution and reliability. However, radar images are easily blurred by sidelobes and background noises, which makes it difficult to extract real target information. In this paper, a sidelobe suppression algorithm based on the point spread function (PSF) and complex-valued neural network has been proposed to discriminate and suppress unwanted sidelobes while maintaining mainlobes referring to targets. To overcome the scarcity of real-world 77 GHz multiple-input multiple-output (MIMO) radar datasets, this paper derives the formula of PSF for 77 GHz MIMO radars in detail and exploits the PSF to generate simulated datasets for training. In addition, to be compatible with the complex-valued radar datasets, a customized neural network model has also been established in this paper. The well-trained neural network is further adopted to suppress sidelobes on real-world radar images. Comprehensive simulations and measurements have proved the superior performance of the proposed method, especially in cases with low signal-to-noise ratio (SNR), large channel mismatches, small target radar Cross-Section (RCS) and large observation angle.

关键词： multiple-input multiple-output radar Sidelobe suppression Noise cancellation Point spread function Complex-valued neural network

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DOD and DOA Estimation in Bistatic Non-Uniform multiple-input multiple-output radar Systems

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IEEE COMMUNICATIONS LETTERS 2012年第11期16卷 1796-1799页

作者： Yao, Bobin Wang, Wenjie Yin, Qinye Xi An Jiao Tong Univ MOE Key Lab Intelligent Networks & Network Secur Xian 710049 Shaanxi Peoples R China

This letter investigates the joint estimation of the direction of departure (DOD) and direction of arrival (DOA) for multi-input multi-output (MIMO) radar systems. A novel estimation method based on non-uniform array configuration is proposed and the practical identifiability of the corresponding parameter is analyzed. The key idea is to use the Doppler diversity to construct a virtual MIMO array. Through the theoretical proof, we demonstrate that the proposed method can provide much stronger parameter identifiability than the conventional ones, and also can improve the parameter estimation performance. Numerical simulations verify the effectiveness of the proposed algorithm.

关键词： multiple-input multiple-output radar non-unform array parameter identifiability angle estimation

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