J4 ›› 2014, Vol. 41 ›› Issue (3): 20-25.doi: 10.3969/j.issn.1001-2400.2014.03.004

• 研究论文 • 上一篇    下一篇

一种利用稀疏表示的距离扩展目标检测新方法

张晓伟;李明;左磊   

  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:2013-03-06 出版日期:2014-06-20 发布日期:2014-07-10
  • 通讯作者: 张晓伟
  • 作者简介:张晓伟(1983-),男,西安电子科技大学博士研究生,E-mail:xwzhang@stu.xidian.edu.cn.
  • 基金资助:

    国家自然科学基金资助项目(61271297, 61272281);博士点基金资助项目(20110203110001);国家部委预研基金资助项目(9140A01060411DZ0101);航空科学基金资助项目(20110181006)

New detection method for extended targets using sparse representation

ZHANG Xiaowei;LI Ming;ZUO Lei   

  1. (National Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an  710071, China)
  • Received:2013-03-06 Online:2014-06-20 Published:2014-07-10
  • Contact: ZHANG Xiaowei

摘要:

针对在高斯白噪声背景下距离扩展目标检测问题,通过构造Sinc基来线性表示距离扩展目标的一维距离像,将稀疏表示理论引入到目标检测中,提出了基于Sinc基的自适应子空间检测器检测新方法.首先由基追踪算法估计噪声功率,再由基追踪去噪算法得到的残余分量估计噪声协方差矩阵,最后通过一阶高斯模型自适应子空间检测器来实现距离扩展目标检测.基于实测宽带雷达回波数据的实验结果表明,所构造的Sinc基可以很好地线性表示距离扩展目标的一维距离像,有效地实现距离扩展目标检测.

关键词: 基追踪去噪, Sinc基, 子空间检测器, 稀疏表示

Abstract:

The problem of detecting extended targets embedded in the Gaussian noise is considered. The Sinc basis is introduced to sparsely represent the high resolution range profile (HRRP) of extended targets. Bringing the sparse representation theory into the target detection, a new method is proposed to solve the problem by the adaptive subspace detector (ASD) based on Sinc basis. Firstly, the noise power is estimated by basis pursuit (BP), then the basis pursuit de-noising (BPDN) is used to estimate the noise covariance by the residues and finally, the ASD of the first order Gaussian model realizes the extended target detection. Experimental results based on the raw data measured by the wideband radar show that the Sinc basis can sparsely represent HRRPs very well and that the proposed method can effectively realize the extended target detection.

Key words: basis pursuit de-nosing, Sinc basis, subspace detector, sparse representation

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