Maximum likelihood SAR autofocus with low-return region

Autofocus algorithms deal with image restoration in a nonideal synthetic aperture radar (SAR) imaging system. We propose a novel autofocus algorithm, denoted as MLA, that is based on maximum likelihood estimation. MLA belongs to a class of autofocus algorithms that rely on a known low-return region in the underlying image. We find conditions under which MLA is equivalent to previous methods belonging to the same class. Simulation results show that when compared to previous methods, MLA performs better both in terms of visual quality of the restored image and mean square error (MSE) of the estimated unknown parameters.