1SYNTHETIC APERTURE RADAR AUTOFOCUS VIA SEMIDEFINITE RELAXATION

imaging amounts to estimating unknown phase errors caused by unknown platform or target motion, or a time- or spatially-varying transmission medium. At the heart of three state-of-the-art autofocus algorithms, namely Phase Gradient Autofocus, Multichannel Autofocus (MCA) and Fourier-domain Multichan-nel Autofocus (FMCA), is the solution of a constant modulus quadratic program (CMQP). Currently, these algorithms solve CMQP by using an eigenvalue relaxation approach. We propose an alternative relaxation approach based on semidefinite pro-gramming, which has recently attracted considerable attention in other signal processing problems. Experimental results show that our proposed methods provide promising performance improvements for MCA and FMCA through an increase in computational complexity. Index Terms—Synthetic aperture radar, Autofocus, Multichan