摘要
由于成像场景可稀疏表示(场景中仅有少数强散射点),针对外辐射源信号波长长,带宽窄的特点,本文提出了基于压缩感知的多发单收无源雷达成像算法,该算法由符合图像统计特性的先验信息构造合理的傅里叶基矩阵,利用lp范数法将带约束条件强散射点增强问题转换为最优化问题,并通过迭代算法快速获得最优解。实验仿真结果表明小转角情况下,本文算法无需充足站点数目,并且能获得较好成像效果。
Passive multistatic radar imaging algorithm is proposed on the basis of compressed sensing since a image scene usually has a few scattering centers. First, this method is used to construct a reasonable Fourier sparse basis matrix via the prior information constrained by the statistical property of SAR image. Then, the point-enhanced problem is transformed into the optimization problem by the using lp norm method. Finally, a fast recursive algorithm is presented to solve the optimization problem. Numerical simulation shows the method has good imaging performance without the request of enough stations under the location of small rotating angle.
出处
《宇航学报》
EI
CAS
CSCD
北大核心
2012年第11期1681-1689,共9页
Journal of Astronautics
基金
国家自然科学基金(60672075)
国家部委基金(9140A07010311BQ02)
教育部博士点基金(20113219110018)
南京理工大学自主科研专项计划资助项目(2010ZDJH05)
关键词
无源雷达成像
多基地雷达
稀疏
压缩感知
Passive radar imaging
Muhistatie radar
Sparsity
Compressed sensing
