On Efficient Maximum Likelihood Algorithm for Clutter Suppression

被引：1

作者：

Zhang, Xinying ^{[1
]}

Wang, Tong ^{[1
]}

Wang, Degen ^{[1
]}

机构：

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

来源：

IEEE SIGNAL PROCESSING LETTERS | 2024年 / 31卷

基金：

国家重点研发计划;

关键词：

Maximum likelihood (ML); majorization-minimization (MM); space-time adaptive processing (STAP); off-grid;

D O I：

10.1109/LSP.2024.3399631

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：

Nonside-looking mode for airborne radar system is important to detect targets. However, the nonlinear distribution of clutter results traditional space-time adaptive processing (STAP) performance degradation. To address the off-grid effect, an effective STAP algorithm is proposed. We first formulate the block-Toeplitz structured clutter covariance matrix (CCM) recovery problem using the stochastic maximum likelihood (ML) criterion. Then, we employ the majorization-minimization (MM) frame to solve the non-convex ML optimization problem. Finally, extensive simulation results evidence the performance of our method.

引用

页码：1399 / 1403

页数：5

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