PEE-Net: Phase Error Estimation Network for Refocusing of Three-Dimensional Rotating Ship Target in SAR Images

In a synthetic aperture radar (SAR) system, the three-dimensional rotation of ship targets in the presence of medium to high sea states could cause Doppler frequency shifts and image defocusing, and even the defocusing phenomenon is space-variant along the range direction would occur. These issues would adversely affect the subsequent interpretation of ship targets in SAR images. This paper proposes a refocusing method based on a phase error estimation network (PEE-Net) to address the refocusing problem of three-dimensional rotating ship targets. The proposed method transforms the defocused complex-valued SAR ship image into the range-Doppler domain, estimates the phase error by range unit using PEE-Net, and compensates for space-variant phase errors. To train the network in an unsupervised manner and avoid the challenging task of obtaining labeling samples of non-cooperative ships, the proposed method introduces the image entropy loss function based on the minimum entropy criterion.