SAR Target Enhancement Method via Prior Information Acquisition and Application

Compressed sensing synthetic aperture radar (SAR) imaging method can use the sparse prior information of the target in the scene to improve the imaging resolution. However, the actual target usually has more structural features, and it is difficult to reconstruct the target accurately if only the sparse prior of the target is used. This paper segmented the location and shape prior information of the target ROI region according to the historical imaging data. By selecting different weighting functions for the clutter region and the target ROI region, a weighting matrix was obtained, which could enhance the target region while suppressing clutter. At the same time, the TV regularization constraint is introduced into the optimization problem to enhance the structural characteristics of the target. Finally, the Augmented lagrange multiplier (ALM) method and Alternate direction multiplier (ADMM) method is used to solve the problem. Experimental results verify the effectiveness of the proposed method.