A Sparsity-Driven Approach for Joint SAR Imaging and Phase Error Correction | IEEE Journals & Magazine | IEEE Xplore

A Sparsity-Driven Approach for Joint SAR Imaging and Phase Error Correction


Abstract:

Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the obser...Show More

Abstract:

Image formation algorithms in a variety of applications have explicit or implicit dependence on a mathematical model of the observation process. Inaccuracies in the observation model may cause various degradations and artifacts in the reconstructed images. The application of interest in this paper is synthetic aperture radar (SAR) imaging, which particularly suffers from motion-induced model errors. These types of errors result in phase errors in SAR data, which cause defocusing of the reconstructed images. Particularly focusing on imaging of fields that admit a sparse representation, we propose a sparsity-driven method for joint SAR imaging and phase error correction. Phase error correction is performed during the image formation process. The problem is set up as an optimization problem in a nonquadratic regularization-based framework. The method involves an iterative algorithm, where each iteration of which consists of consecutive steps of image formation and model error correction. Experimental results show the effectiveness of the approach for various types of phase errors, as well as the improvements that it provides over existing techniques for model error compensation in SAR.
Published in: IEEE Transactions on Image Processing ( Volume: 21, Issue: 4, April 2012)
Page(s): 2075 - 2088
Date of Publication: 09 December 2011

ISSN Information:

PubMed ID: 22167627

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