电子学报 ›› 2016, Vol. 44 ›› Issue (11): 2796-2801.DOI: 10.3969/j.issn.0372-2112.2016.11.032

• 学术论文 • 上一篇    下一篇

基于联合稀疏功率谱恢复的机载雷达稳健STAP算法研究

高志奇, 陶海红, 赵继超   

  1. 西安电子科技大学雷达信号处理国家重点实验室, 陕西西安 710071
  • 收稿日期:2015-07-09 修回日期:2015-10-13 出版日期:2016-11-25 发布日期:2016-11-25
  • 作者简介:高志奇,男,1980年生于内蒙古五原县,博士研究生,讲师,主要研究方向为空时自适应信号处理.E-mail:gzqnd@163.com;陶海红,女,1976年生于安徽亳州,博士,教授,从事信号与信息处理的研究与教学工作,主要研究方向为信号波形优化设计和自适应波束形成及智能方法在信号处理上的应用.
  • 基金资助:

    国家自然科学基金(No.60971108);国家重点基础研究发展计划(973计划)(No.2011CB707001)

Robust STAP Algorithm Based on Joint Sparse Recovery of Clutter Spectrum for Airborne Radar

GAO Zhi-qi, TAO Hai-hong, ZHAO Ji-chao   

  1. National Laboratory of Radar Signal Processing, Xidian University, Xi'an, Shaanxi 710071, China
  • Received:2015-07-09 Revised:2015-10-13 Online:2016-11-25 Published:2016-11-25

摘要:

机载雷达信号的空时自适应处理(STAP,Space-Time Adaptive Processing)需要利用样本数据来估计杂波协方差矩阵.非均匀杂波环境中的离群点会使协方差矩阵的估计出现偏差,从而导致信号相消现象.针对此问题,本文提出一种基于联合稀疏功率谱恢复的STAP算法(JSR-STAP)处理非均匀杂波,以克服离群点对正侧视模式机载雷达的STAP性能的影响.JSR-STAP算法在高分辨稀疏恢复的条件下,利用多快拍间杂波和离群点的分布规律和相关性不同,通过范数选择合适的稀疏恢复系数来实现离群点的抑制.Monte Carlo实验证明JSR-STAP算法的稳健性和动目标检测性能均优于传统的STAP算法.

关键词: 机载雷达, 空时自适应, 稀疏恢复, 离群点

Abstract:

Space-time adaptive processing (STAP) needs to estimate clutter covariance matrix by training sample data.However,this estimation is always corrupted by outliers,which even lead to target self-nulling phenomenon.Hence,a novel robust STAP algorithm based on joint sparse recovery of clutter spectrum is proposed,which can eliminate the influence of outlier.This algorithm is applied in side-looking airborne radar.When the sparse recovery is high resolution,the algorithm exploits the characteristic that distribution and correlation between clutter and outlier are different among multiple snapshots.The norm is employed to select the most suitable sparse recovery coefficients to estimate the clutter spectrum,so outlier can be eliminated effectively.Monte Carlo experiments prove that the proposed algorithm has advantages in robustness and target detection over other conventional STAP algorithms in non-homogeneous clutter environments.

Key words: airborne radar, space-time adaptive processing, sparse recovery, outlier

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