title   
  

SAR moving target imaging in a sparsity-driven framework

Önhon, Özben Naime and Çetin, Müjdat (2011) SAR moving target imaging in a sparsity-driven framework. In: SPIE Optics + Photonics Symposium, Wavelets and Sparsity XIV Conference, San Diego, California, USA

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Official URL: http://dx.doi.org/10.1117/12.893581

Abstract

In synthetic aperture radar (SAR) imaging, sparsity-driven imaging techniques have been shown to provide high resolution images with reduced sidelobes and reduced speckle, by allowing the incorporation of prior information about the scene into the problem. Just like many common SAR imaging methods, these techniques also assume the targets in the scene are stationary over the data collection interval. Here, we consider the problem of imaging in the presence of targets with unknown motion in the scene. Moving targets cause phase errors in the SAR data and these errors lead to defocusing in the corresponding spatial region in the reconstructed image. We view phase errors resulting from target motion as errors on the observation model of a static scene. Based on these observations we propose a method which not only benefits from the advantages of sparsity-driven imaging but also compansates the errors arising due to the moving targets. Considering that in SAR imaging the underlying scene usually admits a sparse representation, a nonquadratic regularization-based framework is used. The proposed method is based on minimization of a cost function which involves regularization terms imposing sparsity on the reflectivity field to be imaged, as well as on the spatial structure of the motion-related phase errors, reflecting the assumption that only a small percentage of the entire scene contains moving targets. Experimental results demonstrate the effectiveness of the proposed approach in reconstructing focused images of scenes containing multiple targets with unknown motion.

Item Type:Papers in Conference Proceedings
Additional Information:Article Number: 813806
Uncontrolled Keywords:SAR imaging, phase errors, regularization-based image reconstruction, sparse signal representation, moving target imaging
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
ID Code:18324
Deposited By:Müjdat Çetin
Deposited On:06 Jan 2012 11:35
Last Modified:05 Apr 2012 11:05

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