基于SA-MUSIC理论的联合稀疏恢复STAP算法

doi:10.3969/j.issn.0372-2112.2015.05.003

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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.

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	王泽涛
	段克清
	谢文冲
	王永良

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

Abstract：

Clutter spectrum in space-time domain is jointly recovered based on subspace-augmented multiple signal classification theory (SA-MUSIC).The performance of space-time adaptive processing (STAP) under small sample size is greatly improved.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.

Key words： airborne radar space-time adaptive processing clutter suppression joint sparse recovery multiple measurement vector

收稿日期: 2013-12-16

ZTFLH:

TN957

基金资助:

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

通讯作者: 王泽涛 E-mail: wangzetao12@126.com

作者简介: 段克清 男,1981出生于河北石家庄,2010年获国防科学技术大学信号与信息处理专业工学博士学位,现为空军预警学院雷达兵器运用工程军队重点实验室博士后,在国内外发表学术论文30余篇,主要研究方向为空时自适应处理、阵列信号处理、稀疏恢复等.E-mail:duankeqing@aliyun.com

引用本文:

王泽涛, 段克清, 谢文冲, 王永良. 基于SA-MUSIC理论的联合稀疏恢复STAP算法[J]. 电子学报, 2015, 43(5): 846-853. WANG Ze-tao, DUAN Ke-qing, XIE Wen-chong, WANG Yong-liang. A Joint Sparse Recovery STAP Method Based on SA-MUSIC. Chinese Journal of Electronics, 2015, 43(5): 846-853.

链接本文:

http://www.ejournal.org.cn/CN/10.3969/j.issn.0372-2112.2015.05.003 或 http://www.ejournal.org.cn/CN/Y2015/V43/I5/846

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