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Proceedings Paper

Localization of scattering centers in radar imaging based on sparsity constraints
Author(s): Suman K. Gunnala; Jeffrey B. Hall; Jonathan Bredow; Saibun Tjuatja
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Paper Abstract

In radar imaging, for example Inverse Synthetic Aperture Radar (ISAR) imaging, a target can be modeled as a collection of scattering centers in the image domain. A method to improve radar image quality through clutter suppression and localization of scattering centers is presented in this paper. The approach is based on localizing the scattering centers by enforcing sparsity constraints through random compressive sampling of the measured data. Sparsity constraint ratio is chosen as a design parameter to achieve the objective. Results show that significant clutter reduction and improvement in localization of scattering centers are achieved at an optimum sparsity constraint ratio.

Paper Details

Date Published: 28 April 2009
PDF: 8 pages
Proc. SPIE 7337, Algorithms for Synthetic Aperture Radar Imagery XVI, 73370J (28 April 2009); doi: 10.1117/12.818952
Show Author Affiliations
Suman K. Gunnala, The Univ. of Texas at Arlington (United States)
Jeffrey B. Hall, The Univ. of Texas at Arlington (United States)
Jonathan Bredow, The Univ. of Texas at Arlington (United States)
Saibun Tjuatja, The Univ. of Texas at Arlington (United States)


Published in SPIE Proceedings Vol. 7337:
Algorithms for Synthetic Aperture Radar Imagery XVI
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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