基于SA-MUSIC理论的联合稀疏恢复STAP算法  

A Joint Sparse Recovery STAP Method Based on SA-MUSIC

作　　者：王泽涛[1,2] 段克清[2] 谢文冲[2] 王永良[2] 

机构地区：[1]国防科学技术大学电子科学与工程学院,湖南长沙410073 [2]空军预警学院,湖北武汉430019

出　　处：《电子学报》2015年第5期846-853,共8页Acta Electronica Sinica

基　　金：国家杰出青年科学基金(No.60925005);国家青年科学基金(No.61102169)

摘　　要：基于子空间扩展多重信号分类(SA-MUSIC)理论对杂波空时二维谱进行联合稀疏恢复,实现小样本情况下空时自适应处理(STAP)性能的显著提升.首先,提出空时导向矢量相关性模型,利用该模型分析杂波在空时二维平面上的稀疏本质,解释用部分空时导向矢量近似整个杂波子空间的合理性.其次,提出基于SA-MUSIC理论的联合稀疏恢复STAP算法(SA-MUSIC-STAP),该算法仅需极少训练样本便可实现对杂波协方差矩阵的准确估计,并实现有效的杂波抑制.仿真实验验证了SA-MUSIC-STAP算法的有效性.Clutter spectrum in space-time domain is jointly recovered based on subspace-augmented multiple signal classifica- tion theory （SA-MUSIC）. The performance of space-time adaptive processing （STAP） under small sample size is greatly im- proved.Firstly,the sparse nature of clutter in space time domain is analyzed using the space-time steering vector correlation model, and the reason of using few space-time steering vectors to represent the whole clutter subspace is given. Secondly, an algorithm named as SA-MUSIC-STAP is proposed to estimate the clutter covariance matrix with much less training samples,then the clutter is effectively suppressed by the new algorithm. Simulation results verified the effectiveness of SA-MUSIC-STAP.

关 键 词：机载雷达 空时自适应处理 杂波抑制 联合稀疏恢复 多观测矢量 

分 类 号：TN957[电子电信—信号与信息处理]