I. Introduction

Synthetic aperture radar (SAR) has recently been and continues to be a sensor of great interest in a variety of remote sensing applications, particularly because it overcomes certain limitations of other sensing modalities. First, SAR is an active sensor using its own illumination. To illuminate a ground patch of interest, the SAR sensor uses microwave signals that provide SAR with the capability of imaging day and night as well as in adverse weather conditions. Due to these features of SAR, SAR image formation has become an important research topic. The problem of SAR image formation is a typical example of inverse problems in imaging. The solution of inverse problems in imaging requires the use of a mathematical model of the observation process. However, such models often involve errors and uncertainties themselves. As a predominant example in SAR imaging, motion-induced errors are reasons for model uncertainties that may cause undesired artifacts in the formed imagery. This type of errors causes phase errors in the SAR data, which result in defocusing of the reconstructed images [1]. Because of the defocusing effect of such errors, the techniques developed for removing phase errors are often called autofocus techniques.