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SAR moving object imaging using sparsity imposing priors

Önhon, Özben Naime and Çetin, Müjdat (2017) SAR moving object imaging using sparsity imposing priors. EURASIP Journal on Advances in Signal Processing . ISSN 1687-6172 (Print) 1687-6180 (Online)

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Official URL: http://dx.doi.org/10.1186/s13634-016-0442-z

Abstract

Synthetic aperture radar (SAR) returns from a scene with motion can be viewed as data from a stationary scene, but with phase errors due to motion. Based on this perspective, we formulate the problem of SAR imaging of motion-containing scenes as one of joint imaging and phase error compensation. The proposed method is based on the minimization of a cost function which involves sparsity-imposing regularization terms on the reflectivity field to be imaged, considering that it admits a sparse representation 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 objects. To incorporate the spatial structure of the phase errors into the problem, we provide three different sparsity-enforcing prior terms. In order to achieve computational gains, we also present a two-step version of our approach, which first determines regions of interest that are likely to contain the moving objects and then applies our sparsity-driven approach for joint image reconstruction and autofocusing in such a spatially constrained setting. Our preliminary experiments demonstrate the effectiveness of this new moving target SAR imaging approach.

Item Type:Article
Uncontrolled Keywords:SAR; Moving object; Sparsity; Group sparsity; Low-rank sparse decomposition
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
ID Code:33796
Deposited By:Müjdat Çetin
Deposited On:09 Sep 2017 21:43
Last Modified:09 Sep 2017 21:43

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