SAR imaging with frequency band gaps based on sparse regularization

We consider the problem of SAR imaging with frequency band gaps. Frequency gaps in the phase history data can cause severe degradation of image quality. In this paper, we apply sparse regularization methods to reconstruct SAR images from frequency-gapped data. Two regularization methods are evaluated, i.e., the l₁ regularization method and the sparse maximum a posteriori (SMAP) estimation method. Both sparse and complicated scenes are considered in this paper. Experimental results on real data for man-made target and SAR interferometry are presented.