Autofocus for Synthetic Aperture Radar

Abstract

In this thesis, I compare the performance of three different autofocus techniques for Synthetic Aperture Radar (SAR). The focusing is done by estimating phase errors in SAR data. The first one, the Phase Gradient Autofocus, is the most popular in the industry, it has been around for more than 20 years and it relies on the redundancy of the phase error in the SAR images. The second one, the Entropy-based minimization, uses measurements of image sharpness to focus the images and it has been available for about 10 years. The last, the Phase-space method, uses the Wigner transform and the ambiguity function of the SAR data to estimate the phase perturbations and it was recently introduced. Additionally, I develop a criteria for filtering the data for the cases in which the Phase-space method does not capture the entirety of the error.