Weighted least-squares estimation of phase errors for SAR/ISAR autofocus

A new method of phase error estimation that utilizes the weighted least-squ ares (WLS) algorithm is presented for synthetic aperture radar (SAR)/invers e SAR (ISAR) autofocus applications. The method does not require that the s ignal in each range bin be of a certain distribution model, and thus it is robust for many kinds of scene content. The most attractive attribute of th e new method is that it can be used to estimate all kinds of phase errors, no matter whether they are of low order, high order, or random. Compared wi th other methods, the WLS estimation is optimal in the sense that it has th e minimum variance of the estimation error. Excellent results have been obt ained in autofocusing and imaging experiments on real SAR and ISAR data.