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Co-Located MIMO Radar Target Detection in Cluttered and Noisy Environment Based on 2D Block Sparse Recovery
IEEE Transactions on Signal Processing ( IF 5.4 ) Pub Date : 2021-06-07 , DOI: 10.1109/tsp.2021.3086362
Xingyu Lu , Bangzhen Xu , Tat Soon Yeo , Weimin Su , Hong Gu

In the co-located multiple input multiple output (MIMO) radar, the matched filter receiver suffers from high range sidelobes, since the waveforms originating from different transmitters cannot be fully orthogonal. Traditional sparse recovery based receivers can suppress the sidelobes by assuming the sparsity of range profiles. However, in most practical situations, the range profile is not sparse due to the presence of clutter. In this paper, an effective co-located MIMO radar target detection algorithm is proposed based on modified smoothed- $l_0$ norm sparse recovery, by exploiting the 2D block sparsity of the range-Doppler profiles of targets corresponding to different transmit-receive pairs. The proposed method can enhance the target detection performance in co-located MIMO radar system, especially for those weak targets which may be overwhelmed by high-level sidelobes of strong targets and clutters, without sacrificing computational efficiency. With a well-designed regularization approach and an adaptive regularization parameter update technique, the proposed method is also robust in noisy environment. Simulation and experimental results validate the effectiveness of the proposed method.

中文翻译:

基于二维块稀疏恢复的杂乱噪声环境下共定位MIMO雷达目标检测

在协同定位的多输入多输出 (MIMO) 雷达中,匹配滤波器接收机受到高范围旁瓣的影响,因为源自不同发射机的波形不能完全正交。传统的基于稀疏恢复的接收器可以通过假设距离分布的稀疏性来抑制旁瓣。然而,在大多数实际情况下,由于杂波的存在,距离剖面并不稀疏。本文提出了一种基于修正平滑的有效协同定位 MIMO 雷达目标检测算法。 $l_0$范数稀疏恢复,通过利用对应于不同发射-接收对的目标的距离-多普勒轮廓的二维块稀疏性。所提出的方法可以提高协同定位 MIMO 雷达系统中的目标检测性能,特别是对于那些可能被强目标和杂波的高级旁瓣淹没的弱目标,而不会牺牲计算效率。通过精心设计的正则化方法和自适应正则化参数更新技术,所提出的方法在嘈杂环境中也具有鲁棒性。仿真和实验结果验证了所提出方法的有效性。
更新日期:2021-07-02
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