Clutter suppression methods based on reduced-dimension transformation for airborne passive radar with impure reference signals

被引：4

作者：

Deng, Yaqi ^{[1
]}

Zhang, Saiwen ^{[1
]}

Zhu, Qiuxiang ^{[1
]}

Zhang, Lincheng ^{[1
]}

Li, Wenguo ^{[1
]}

机构：

[1] Hunan City Univ, Coll Informat & Elect Engn, Yiyang, Peoples R China

来源：

JOURNAL OF APPLIED REMOTE SENSING | 2021年 / 15卷 / 01期

基金：

中国国家自然科学基金;

关键词：

airborne radar; passive radar; reference signal; space-time adaptive processing; sparse recovery; STAP;

D O I：

10.1117/1.JRS.15.016514

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

For an airborne passive radar with impure reference signals, the clutter caused by multipath (MP) signals involved in the reference channel (MP clutter) corrupts the space-time adaptive processing performances. To eliminate the influence of the MP clutter, two clutter suppression methods based on reduced-dimension (RD) transformation are proposed herein. RD transformation is exploited to reduce the size of the sparse recovery dictionary. Subsequently, the sparse recovery problem is revised, and the MP clutter is suppressed using the least mean square (LMS) algorithm and the exponentially forgetting window LMS algorithm. Compared with the existing L-1-based recursive least square algorithm, the proposed algorithms significantly reduce computational complexity without degrading the MP clutter suppression performance. In addition, the proposed algorithms provide more robust characteristics to the errors in prior knowledge than the modified blind equalization method. A range of simulations is conducted to test the proposed algorithms. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)

引用

页数：18

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