A Clutter Suppression Algorithm via Weighted l2 Penalty for Airborne Radar

被引：7

作者：

Liu, Cheng ^{[1
]}

Wang, Tong ^{[1
]}

Zhang, Shuguang ^{[1
]}

Ren, Bing ^{[1
]}

机构：

[1] Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Peoples R China

来源：

IEEE SIGNAL PROCESSING LETTERS | 2022年 / 29卷

基金：

国家重点研发计划;

关键词：

Multiple measurement vectors; space-time adaptive processing; sparsity; weighted penalty; SIMULTANEOUS SPARSE APPROXIMATION;

D O I：

10.1109/LSP.2022.3187347

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this letter, to improve the performance of the space-time adaptive processing (STAP) filter with finite training samples, a novel algorithm with multiple measurement vectors (MMV) based on sparse recovery (SR) is proposed. Compared with traditional SR STAP algorithms, we utilize the knowledge of Capon spectrum to design a weighted l(2)-normpenaltywhich can better approximate the original l(0)-norm. Besides, the proposed algorithm has fast convergence performance and closed-form analytic solution in each iteration. Simulation results demonstrate the effectiveness and great performance of the proposed method.

引用

页码：1522 / 1525

页数：4

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