基于小波包算法的压缩传感SAR成像方法  

A Compressive Sensing SAR Imaging Approach Based on Wavelet Package Algorithm

作　　者：时燕[1] 陈迪荣[1] 

机构地区：[1]北京航空航天大学数学与系统科学学院,北京100191

出　　处：《雷达学报（中英文）》2013年第2期218-225,共8页Journal of Radars

基　　金：国家自然科学基金(11171014);国家973计划项目(2010CB731900)资助课题

摘　　要：压缩传感SAR成像能够大量减小采样率和数据量,但只对稀疏场景有效。该文提出基于小波包训练稀疏表示基的压缩传感SAR成像方法。该方法通过对同类型的SAR图像进行小波包训练,在小波包库中选择能够稀疏表示该类SAR场景的稀疏表示基,并通过求解1l范数最小化问题重构SAR场景反射系数。文中提出的方法在严重降采样下仍能够实现无模糊的SAR成像,仿真数据成像结果表明该文方法具有较好的效果。Compressive sensing SAR imaging can significantly reduce the sampling rate and the amount of data required, but it is essential only in the case where the reflection coefficients of a SAR scene are sparse. This paper proposes a compressive sensing SAR imaging method based on wavelet packet sparse representation. The wavelet packet algorithm is used to choose the most sparse representation of the SAR scene by training the same type of SAR images. By solving for the minimum 11 norm optimization, the SAR scene reflection coefficients can be reconstructed. Unambiguous SAR images can be produced with the proposed method, even with fewer samples. SAR data simulation experiments demonstrate the efficiency of the proposed method.

关 键 词：压缩传感 SAR成像 小波包 稀疏表示 稀疏度 

分 类 号：TN957.52[电子电信—信号与信息处理]