Fast SAR autofocus based on convolutional neural networks
Autofocus is a key technology for high-resolution synthetic aperture radar imaging.However,traditional SAR auto-focus methods require too many iterations,have low computational efficiency,and are unsuitable for on-orbit processing.This paper proposes a fast SAR autofocus method based on convolutional neural networks.This method utilizes CNNs to learn the mapping from defocused images to focused images,mainly designed to correct the azimuth phase errors.It has a real-time per-formance and is more suitable for on-orbit processing since it does not need to iterate or adjust parameters in the testing phase.Experimental results on real SAR data show that our proposed method has the highest focusing quality and speed.
万方数据
维普
