Phase-Preserving Ambiguity Removal of Staggered SAR Image Based on Pixel-Wise Reinforcement Learning.

Staggered SAR is an advanced radar mode which can get the ability of high azimuth resolution and wide range swath simultaneously. Due to the serious spectrum-aliasing, the azimuth ambiguity occurs in the imaging result and brings the wrong amplitude and phase. To reconstruct the images without ambiguity, traditional model-driven methods and data-driven methods cannot have good performance on removing the artifacts and maintaining the real targets meanwhile. In this paper, we consider this task as a pixels process problem and then propose a pixel-wise deep reinforcement learning method to handle it. The proposed method obtains the best comprehensive performance comparing with other method. In addition, its validity is also verified in experiment.