基于块稀疏矩阵恢复的MIMO雷达扩展目标高分辨成像算法

doi:10.12305/j.issn.1001-506X.2021.03.07

Abstract

Abstract:

In order to solve the problems of high computational complexity and low imaging quality for extended targets in existing multiple input multiple output (MIMO) radar sparse recovery imaging algorithms, a high resolution imaging algorithm for MIMO radar extended targets based on block sparse matrix recovery is proposed. By introducing the block sparse feature of target, the imaging quality of spatial extended target is improved. Firstly, by constructing the range and azimuth sensing matrices, the block sparse matrix restoration model of target scattering coefficient estimation is established. Then, the block sparse features of the target are extracted by sequential order one negative exponential (SOONE) function. Finally, the gradient projection algorithm is used to solve the norm optimization problem of block sparse matrix, and the high-quality image of the target is obtained under the condition of under sampling. Compared with the traditional imaging algorithms, the proposed algorithm can achieve high-resolution imaging of extended targets while reducing the amount of data sampling, and has higher accuracy, robustness and lower computational complexity. Simulation experiments verify the effectiveness of the proposed imaging algorithm.

Key words: multiple input multiple output (MIMO) radar, high resolution imaging, sparse matrix recovery, block sparse

CLC Number:

TN957.51

Tao PU, Ningning TONG, Weike FENG, Liang FANG, Xiaoyang GAO. Extended target high resolution imaging algorithm for MIMO radar based on block sparse matrix recovery[J]. Systems Engineering and Electronics, 2021, 43(3): 647-655.

Figures/Tables 11

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References 24

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算法	时间/s
一维SL0	12.08
一维GP-SOONE	14.17
2D SL0	0.01
2D GP-SOONE	0.03
分块2D GP-SOONE	0.48

算法	RMSE
算法	场景1	场景2
BP	2.56	2.31
2D SL0	0.60	0.66
2D GP-SOONE	0.31	0.25
分块2D GP-SOONE	0.16	0.17

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Extended target high resolution imaging algorithm for MIMO radar based on block sparse matrix recovery

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