基于稀疏信号处理的合成孔径雷达(SAR)成像方法可以使SAR图像特征得到增强。为了减小内存占用和计算量,在稀疏SAR 成像过程中常采用基于传统成像算法的方位距离解耦算子。极坐标格式算法(PFA)是传统的聚束SAR成像算法,文中将PFA引入到稀疏聚束SAR成像模型之中,在稀疏重构时使用基于PFA的方位距离解耦算子来替代观测矩阵及其共轭转置,达到减少内存和计算量的目的;同时,可以使SAR图像得到增强。实际数据的处理结果验证了该方法的有效性。

Sparse synthetic aperture radar (SAR) imaging method can enhance the SAR images. Sparse SAR imaging based on measurement matrix can cause huge memory and computational costs. To avoid it, traditional matched filtering method based azimuth-range decoupled operators are adopted in sparse SAR imaging. Polar format algorithm (PFA) is used in spotlight SAR imaging. In this paper, we introduce PFA to sparse spotlight SAR imaging. In the iteration of sparse spotlight SAR imaging, we use PFA based operators to substitute the measurement matrix and its conjugate transpose. The memory and computational costs are reduced. The SAR images are enhanced. Experimental results via real data verify the presented method.

TN957. 52