Comparison of parametric sparse recovery methods for ISAR image formation  

作　　者：RAO Wei LI Gang WANG XiQin XIA XiangGen 

机构地区：[1]Department of Electronic Engineering,Tsinghua University [2]Department of Electrical and Computer Engineering,University of Delaware [3]Department of Electronic Engineering,Chonbuk National University

出　　处：《Science China(Information Sciences)》2014年第2期151-162,共12页中国科学（信息科学）（英文版）

基　　金：supported in part by National Natural Science Foundation of China(Grant Nos.41271011,40901157);National Basic Research Program of China(973 Program)(Grant No.2010CB731901);Program for New Century Excellent Talents in University(Grant No.NCET-11-0270);Tsinghua University Initiative Scientific Research Program;supported in part by National Science Foundation(Grant NoCCF-0964500);Air Force Ofce of Scientific Research(AFOSR)(Grant No.FA9550-12-1-0055)

摘　　要：A parametric sparse representation model of the inverse synthetic aperture radar （ISAR） signal has been proposed recently, and the ISAR signal is decomposed as a summation of many basis-signals determined by the target rotation rate. Based on the parametric sparse representation model, several sparsity^driven algorithms are proposed to retrieve both the target rotation rate and the ISAR image. In this paper, four parametric sparse recovery algorithms are compared mainly in three aspects： the accuracy of the rotation rate estimation, the ISAR image quality and the computational load. Numerical examples are presented to show the advantages and disadvantages for each method.A parametric sparse representation model of the inverse synthetic aperture radar （ISAR） signal has been proposed recently, and the ISAR signal is decomposed as a summation of many basis-signals determined by the target rotation rate. Based on the parametric sparse representation model, several sparsity^driven algorithms are proposed to retrieve both the target rotation rate and the ISAR image. In this paper, four parametric sparse recovery algorithms are compared mainly in three aspects： the accuracy of the rotation rate estimation, the ISAR image quality and the computational load. Numerical examples are presented to show the advantages and disadvantages for each method.

关 键 词：ISAR imaging parametric sparse representation adaptive sparse recovery matching pursuit 

分 类 号：TN957.52[电子电信—信号与信息处理]