SAR Image Autofocusing using Wirtinger calculus and Cauchy regularization

TL;DR

This paper introduces a novel SAR image autofocusing method that combines Wirtinger calculus for complex variable optimization with Cauchy regularization to enhance image reconstruction and phase error correction.

Contribution

It presents a new optimization framework that jointly reconstructs SAR images and corrects phase errors using Wirtinger calculus and Cauchy regularization, improving autofocusing performance.

Findings

Effective autofocusing on simulated and real SAR images

Improved image quality with Cauchy regularization

Successful joint reconstruction and phase error correction

Abstract

In this paper, an optimization model using Cauchy regularization is proposed for simultaneous SAR image reconstruction and autofocusing. A coordinate descent framework in which the desired image and the phase errors are optimized alternatively is designed to solve the model. For the subproblem of estimating the image, we utilize the techniques of Wirtinger calculus to directly minimize the cost function which involves complex variables. We also utilise a state-of-the-art, sparsity-enforcing Cauchy regularizer. The proposed method is demonstrated to give impressive autofocusing results by conducting experiments on both simulated scene and real SAR image.