Performance of Compressed Sensing MIMO Radar Based on Low-Rank Matrix Recovery

被引：0
|
作者：
McMullen, Byron [1 ]
Kim, Seung-Jun [1 ]
机构：
[1] Univ Maryland Baltimore Cty, Dept Comp Sci & Elect Engn, Baltimore, MD 21250 USA
来源：
2022 IEEE MILITARY COMMUNICATIONS CONFERENCE (MILCOM) | 2022年
关键词：
MIMO radar; low-rank matrix recovery; random modulator pre-integrator; compressed sensing;
D O I：
10.1109/MILCOM55135.2022.10017622
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Compressed sensing (CS) techniques have been successfully applied to multi-input multi-output (MIMO) radars to drastically reduce the sampling rates required for acquiring data. In this work, a CS MIMO radar is derived by employing a matrix recovery algorithm exploiting the low-rank structure of the data matrix based on linearly compressed measurements. Compared to a MIMO radar based on low-rank matrix completion, the proposed approach is seen to provide superior data reconstruction and target estimation performance at lower sampling rates.
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页数：6
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