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
收藏
页码：1522 / 1525
页数：4
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