首页 | 本学科首页   官方微博 | 高级检索  
     

利用压缩感知的短孔径高分辨ISAR成像方法
引用本文:全英汇,张磊,刘亚波,张龙,保铮. 利用压缩感知的短孔径高分辨ISAR成像方法[J]. 西安电子科技大学学报(自然科学版), 2010, 37(6): 1022-1026+1110. DOI: 10.3969/j.issn.1001-2400.2010.06.008
作者姓名:全英汇  张磊  刘亚波  张龙  保铮
作者单位:(西安电子科技大学 雷达信号处理国家重点实验室,陕西 西安710071)
基金项目:国家自然科学基金资助项目(61001211);国家部委预研基金资助项目(9140C0102100902);陕西省自然科学基金资助项目(2009JQ8022)
摘    要:压缩感知理论揭示:对于稀疏信号可以利用非常有限的观测数据对信号本身进行精确恢复.基于此思路提出了一种利用短孔径有限数据实现高分辨逆合成孔径雷达成像的新方法,将逆合成孔径雷达成像转换为利用正交基重构稀疏信号的问题,然后利用压缩感知对目标像高分辨优化重建.同时,根据压缩感知理论对新成像方法的分辨率理论上界进行了推导.对舰船和机动飞机的实测数据的处理结果验证了新方法的有效性和稳健性.

关 键 词:逆合成孔径雷达   压缩感知   稀疏信号重构  
收稿时间:2009-11-24

Method for achieving high resolution ISAR imaging with short aperture data via compressed sensing
QUAN Ying-hui,ZHANG Lei,LIU Ya-bo,ZHANG Long,BAO Zheng. Method for achieving high resolution ISAR imaging with short aperture data via compressed sensing[J]. Journal of Xidian University, 2010, 37(6): 1022-1026+1110. DOI: 10.3969/j.issn.1001-2400.2010.06.008
Authors:QUAN Ying-hui  ZHANG Lei  LIU Ya-bo  ZHANG Long  BAO Zheng
Affiliation:(National Lab. of Radar Signal Processing, Xidian Univ., Xi'an  710071, China)
Abstract:Compressed sensing suggests that exact recovery of a sparse signal is possible from very limited measurements. Based on this idea, a new method for high-resolution inversed synthetic aperture radar (ISAR) imaging with short aperture data is presented. This approach converts ISAR imaging into the problem of reconstructing the sparse signal with an orthogonal basis, then compressed sensing is applied to reconstruct the high resolution image optimally. And a conceptive upper bound of resolution is derived in detail. Experiments using real ISAR data of ship and plane are performed, whose results confirm the validity of the proposal in high resolution ISAR imaging with limited data.
Keywords:inverse synthetic aperture radar   compressed sensing   sparse signal reconstruction  
本文献已被 万方数据 等数据库收录!
点击此处可从《西安电子科技大学学报(自然科学版)》浏览原始摘要信息
点击此处可从《西安电子科技大学学报(自然科学版)》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号