Sparsity-driven coupled imaging and autofocusing for interferometric SAR

Official URL: http://risc01.sabanciuniv.edu/record=b1817225 (Table of Contents)

In this thesis, we present a new joint image enhancement and reconstruction method and a software processing tool for SAR Interferometry. First, we propose a sparsity-driven method for coupled image formation and autofocusing based on multi-channel data collected in interferometric synthetic aperture radar (IfSAR). Relative phase between SAR images contains valuable information. For example, it can be used to estimate the height of the scene in SAR Interferometry. However, this relative phase could be degraded when independent enhancement methods are used over SAR image pairs. Previously, Ramakrishnan, Ertin, and Moses proposed a coupled multi-channel image enhancement technique, based on a dual descent method, which exhibits better performance in phase preservation compared to independent enhancement methods. Their work involves a coupled optimization formulation that uses a sparsity enforcing penalty term as well as a constraint tying the multichannel images together to preserve the cross-channel information. In addition to independent enhancement, the relative phase between the acquisitions can be degraded due to other factors as well, such as platform location uncertainties, leading to phase errors in the data and defocusing in the formed imagery. The performance of airborne SAR systems can be affected severely by such errors. We ii propose an optimization formulation that combines Ramakrishnan et al.'s coupled IfSAR enhancement method with the sparsity-driven autofocus (SDA) approach of Önhon and Çetin to alleviate the effects of phase errors due to motion errors in the context of IfSAR imaging. Our method solves the joint optimization problem with a Lagrangian optimization method iteratively. In our preliminary experimental analysis, we have obtained results of our method on synthetic SAR images and compared its performance to existing methods. As a second contribution of this thesis, we have developed a software toolbox for end-to-end interferometric SAR processing. This toolbox is capable of performing the fundamental steps of SAR Interferometry Processing. The thesis contains the detailed explanation of the algorithms implemented in the SAR Interferometry Toolbox. Test results are also provided to demonstrate the performance of the Toolbox under different scenarios.