基于稀疏恢复的空时二维自适应处理技术研究现状  

An Overview on Sparse Recovery-based STAP

作　　者：马泽强[1] 王希勤[1] 刘一民[1] 孟华东[1] 

机构地区：[1]清华大学电子工程系,北京100084

出　　处：《雷达学报（中英文）》2014年第2期217-228,共12页Journal of Radars

基　　金：国家自然科学基金(61201356);国家973项目(2010CB731901)资助课题

摘　　要：该文介绍了基于稀疏恢复(Sparse Recovery,SR)的空时2维自适应处理技术(Space-Time Adaptive Processing,STAP)的研究背景、意义和具体实现方法。首先探讨了将稀疏恢复引入STAP领域的意义和价值,揭示了在杂波非均匀环境下引入稀疏恢复的潜在优势,分析了稀疏恢复STAP技术的数学意义。并在此基础上,系统梳理和总结了该研究方向的研究现状和已有成果,介绍了均匀线性阵列条件下稀疏恢复STAP技术的基本框架、多观测向量问题、格点对不准问题、直接数据域稀疏恢复STAP、共型阵条件下基于稀疏恢复的STAP方法等具体研究内容。最后,总结了基于稀疏恢复STAP技术的框架和结构,并以此为基础对后续研究工作的方向和前景进行了探讨。This paper gives a brief review on the Sparse-Recovery （SR）-based Space-Time Adaptive Processing （STAP） technique. First, the motivation for introducing sparse recovery into STAP is presented. Next, the potential advantages and mathematical explanation of the sparse-recovery-based STAP are discussed. A major part of this paper presents the state-of-art research results in spatio-temporal spectrum-sparsity-based STAP, including the basic frame, off-grid problem, multiple measurement vector problem, and direct domain problem. The sparse-recovery-based STAP on conformal array problem is also introduced. Finally, a summary of sparse-recovery-based STAP is provided, and the problems that need to be solved and some potential research areas are discussed.

关 键 词：机载雷达 杂波抑制 稀疏恢复(SR) 空时自适应处理(STAP) 

分 类 号：TN95[电子电信—信号与信息处理]