Localization of scattering centers in radar imaging based on sparsity constraints

Suman K. Gunnala; Jeffrey B. Hall; Jonathan Bredow; Saibun Tjuatja

doi:10.1117/12.818952

28 April 2009 Localization of scattering centers in radar imaging based on sparsity constraints

Suman K. Gunnala, Jeffrey B. Hall, Jonathan Bredow, Saibun Tjuatja

Proceedings Volume 7337, Algorithms for Synthetic Aperture Radar Imagery XVI; 73370J (2009) https://doi.org/10.1117/12.818952
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

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.

Citation Download Citation

Suman K. Gunnala, Jeffrey B. Hall, Jonathan Bredow, and Saibun Tjuatja "Localization of scattering centers in radar imaging based on sparsity constraints", Proc. SPIE 7337, Algorithms for Synthetic Aperture Radar Imagery XVI, 73370J (28 April 2009); https://doi.org/10.1117/12.818952

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