摘要
为实现快速、高分辨率逆合成孔径雷达(ISAR)成像,利用目标的内在块稀疏结构信息,提出一种迭代加权L2/L1范数块稀疏重构ISAR成像算法。构建ISAR稀疏成像模型,将ISAR成像问题转化为稀疏信号重构问题后,在每次迭代中求解用于下次迭代的权值向量解,从而实现高分辨率ISAR成像。实验结果表明,相比BP、OMP、SBL算法,该算法可以改善成像质量,提高重构效率。
In order to realize fast and high resolution Inverse Synthetic Aperture Radar(ISAR)imaging,an iterative weighted L2/L1 norm block sparse recovery algorithm for ISAR imaging is proposed based on the target’s intrinsic block sparse structure information.After constructing the ISAR sparse imaging model and transforming the ISAR imaging problem into the sparse signal recovery problem,the weighted vector solution for the next iteration is solved in each iteration,and then the high resolution ISAR imaging is realized.Experimental results show that compared with BP,OMP and SBL,the proposed algorithm can improve the image quality and recovery efficiency.
作者
冯俊杰
张弓
FENG Junjie;ZHANG Gong(College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;School of Electrical Engineering,Liupanshui Normal University,Liupanshui,Guizhou 553004,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2018年第11期234-238,共5页
Computer Engineering
基金
国家自然科学基金(61471191)
航空科学基金(20152052026)
贵州省科学技术基金(黔科合LH字[2014]7471号)
贵州省重点学科项目(ZDXK201535)
关键词
逆合成孔径雷达
迭代加权
L2/L1范数
稀疏信号重构
稀疏成像
Inverse Synthetic Aperture Radar(ISAR)
iterative weighted
L2/L1 norm
sparse signal recovery
sparse imaging
