ISAR autofocus based on image entropy optimization algorithm

An improved autofocus method is presented based on minimum-entropy criterion for inverse synthetic aperture radar imaging. The phase-error corrections are initialized by dominant scatter algorithm, and an iterative method is derived to minimize the image entropy. A local quadratic curve is constructed to gradually approach the extremun of the image entropy function, though minimizing the image entropy, the phase-errors which corrupt the image are obtained. Finally, real ISAR data are used to validate the effectiveness and robustness of this method. The results demonstrate that the proposed method has better effect of autofocusing under low SNR.