A Novel Method for Multi-Targets ISAR Imaging Based on Particle Swarm Optimization and Modified CLEAN Technique

作     者：Liu, Lei Zhou, Feng Tao, Mingliang Zhang, Zijing 

作者机构：Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China 

出 版 物：《IEEE SENSORS JOURNAL》 (IEEE Sensors J.)

年 卷 期：2016年第16卷第1期

页      面：97-108页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0804[工学-仪器科学与技术] 0702[理学-物理学] 

基　　金：National Natural Science Foundation of China [61201283, 61471284, 612310107, 61522114] NSAF [U1430123] Foundation for the Author of National Excellent Doctoral Dissertation of PR China Program for New Century Excellent Talents in University [NCET-12-0916] 

主　　题：Inverse synthetic aperture radar (ISAR) multi-targets particle swarm optimization (PSO) modified CLEAN clustering algorithm 

摘      要：In multi-targets inverse synthetic aperture radar (ISAR) imaging, range profiles of different target are coupled together, resulting in the failure of traditional mono-target imaging method. A novel multi-targets ISAR imaging method based on particle swarm optimization (PSO) and modified CLEAN technique is proposed in this paper. First, multi-targets are modeled as several separated group-targets in which translational motion of each target is analogous. And then, translational motion of each group-target is modeled as a polynomial, and the polynomial coefficient vector is estimated via the PSO-based iteration. Furthermore, a well-focused image of the group-target can be obtained and extracted via the proposed modified CLEAN technique. Meanwhile, each target can be segmented and extracted based on clustering number estimation and K-means clustering algorithm. Finally, better focused image of each target would be obtained through further traditional mono-target imaging processing. Experimental results verify the validity of the proposed method.