Bayesian iterative reweighted sparse autofocus array SAR imaging method

The invention discloses a Bayesian iterative reweighted sparse autofocus array synthetic aperture radar (SAR) imaging method. The Bayesian iterative reweighted sparse autofocus array SAR imaging method aims at the influence of phase errors existing in array SAR echo signals on imaging results. Based on a traditional sparse autofocus Bayesian recovery via iterative minimum (SAFBRIM) algorithm, a linear measurement matrix of scattering coefficients in the array SAR original echo signals and an observation scene target space is established, norm items in a cost function in the algorithm are subjected to iterative adaptive reweighted processing, pulse compression and equidistant surface division are carried out on a distance direction, and then each equidistant two-dimensional surface is estimated. According to the Bayesian iterative reweighted sparse autofocus array synthetic aperture radar (SAR) imaging method, different weighting coefficients are given to each norm item, and then imagesare reconstructed, so th