An Adaptive Scalloping Suppression Method for ScanSAR Images Based on the Kalman Filter

The synthetic aperture radar scan (ScanSAR) mode can change the antenna angle during operation and obtain a wide swath by scanning multiple strips at one time. However, due to discontinuous working in azimuth, the scalloping effect in ScanSAR will degrade the image quality. In this article, a novel adaptive scalloping suppression method is proposed by analyzing the complex scene as well as the scalloping distribution. First, the images of the various types of scenes are preprocessed so that the distribution of subimages satisfies the Kalman filter conditions. Then, the problem of space-variant property is solved by performing adaptive blocking in the range direction. Finally, the Kalman filtering algorithm is introduced to process the scalloping in each subblock separately, and the processed subblocks are fused to obtain the final result. The proposed method is verified by the real ScanSAR images of GF-3. Experimental results show that the proposed method is more efficient for scalloping suppression than the existing ones for both general and complex scenes and has clear improvement for large-scale images with strong scalloping, which fully verifies the robustness and adaptability of the proposed method.