电子学报 ›› 2014, Vol. 42 ›› Issue (3): 424-431.DOI: 10.3969/j.iss.0372-2012-2014.03.002

• 学术论文 • 上一篇    下一篇

稳健的多通道SAR/GMTI通道盲均衡算法

田斌1, 朱岱寅2, 吴迪2, 淘满意3, 朱兆达2   

  1. 1. 西安电子工程研究所, 陕西西安 710100;
    2. 南京航空航天大学电子信息工程学院, 江苏南京 210016;
    3. 上海卫星工程研究所, 上海 200240
  • 收稿日期:2012-07-14 修回日期:2013-03-05 出版日期:2014-03-25 发布日期:2014-03-25
  • 作者简介:田斌 男,1983年7月出生于陕西省西安市周至县.于南京航空航天大学获博士学位.现工作于西安电子工程研究所.主要从事雷达系统设计工作.E-mail:tianbin218@163.com
  • 基金资助:

    国家自然科学基金(No.61071165);教育部新世纪优秀人才支持计划(No.NCET-09-0069)资助课题;中央高校基本科研业务费专项基金(No.NS2012097);教育部博士点基金(No.20123218120021)

Robust Channel Blind Equalization Algorithm for Multi-Channel SAR/GMTI System

TIAN Bin1, ZHU Dai-yin2, WU Di2, TAO Man-yi3, ZHU Zhao-da2   

  1. 1. Xi'an Electronics and Engineering Research Institute, Xi'an, Shaanxi 710100, China;
    2. College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China;
    3. Shanghai Institute of Satellite Engineering, Shanghai 200240, China
  • Received:2012-07-14 Revised:2013-03-05 Online:2014-03-25 Published:2014-03-25

摘要: 对于实际的多通道合成孔径雷达(Synthetic Aperture Radar,SAR)系统,各接收通道响应之间不可避免地存在着一定程度的幅度和相位误差,为了得到较为满意的地面动目标显示(Ground Moving Target Indication,GMTI)性能,通常都会在杂波抑制之前对通道间的幅度相位误差进行有效地校正.本文在基于回波数据相关矩阵特征分解的通道盲均衡算法基础上,结合降维处理技术及中值估计方法,提出一种稳健的多通道SAR/GMTI通道盲均衡算法.实测数据实验结果表明:与原通道盲均衡算法相比,本文所提算法不但收敛速度快,而且算法的有效性不受样本集中目标信号的影响.

关键词: 地面动目标检测, 通道盲均衡, 降维处理, 中值估计

Abstract: The channel mismatch is often inevitable for the actual multi-channel synthetic aperture radar/ground moving target indication (SAR/GMTI) system.Consequently,to enhance GMTI performance,the channel mismatch must be effectively calibrated.A robust channel blind equalization algorithm is investigated.This proposed algorithm is on the basis of the classical channel blind equalization algorithm with eigen-decomposition of data covariance matrix,and combines reduced-dimension processing and median estimate.Experimental results on measured SAR data demonstrate that compared with the conventional algorithm,this proposed algorithm not only shows a faster convergence rate but also exhibits convergence-robustness to targets in the training sample data.

Key words: ground moving target detection (GMTI), channel blind equalization, reduced-dimension processing, median estimate

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