现代电子技术2017，Vol.40Issue(23)：1-5,5.DOI:10.16652/j.issn.1004-373x.2017.23.001
一种优化稀疏分解的雷达目标识别方法
A radar target recognition method based on optimized sparse decomposition
摘要
Abstract
For the huge radar echo data in radar target recognition,the sparse decomposition method is utilized to perform the sparse processing for the echo data. The matching pursuit algorithm in sparse decomposition has the problem of complex com-putation and large calculated quantity,so the strong global searching ability and fast convergence speed of the particle swarm op-timization(PSO)algorithm are adopted to optimize the search process of the optimal atom. Since the PSO algorithm is easy to fall into the local optimization,an improved solution for the adaptive change of inertia weight is proposed. The sparse representation experiment of radar′s high resolution range profile(HRRP)signal was performed with simulation. It is found that the matching pur-suit algorithm based on PSO can significantly shorten the time of matching pursuit,and the adaptive change method of inertia weight can solve the "prematurity " problem of PSO algorithm effectively.关键词
稀疏分解/粒子群优化/自适应变化/高分辨率距离像Key words
sparse decomposition/particle swarm optimization/adaptive change/high resolution range profile分类
信息技术与安全科学引用本文复制引用
赵东波,李辉..一种优化稀疏分解的雷达目标识别方法[J].现代电子技术,2017,40(23):1-5,5.基金项目
国家自然科学基金资助项目(61571364) （61571364）
