Limited persistence models for SAR automatic target recognition

Nithin Sugavanam; Emre Ertin

doi:10.1117/12.2264744

28 April 2017 Limited persistence models for SAR automatic target recognition

Nithin Sugavanam, Emre Ertin

Proceedings Volume 10201, Algorithms for Synthetic Aperture Radar Imagery XXIV; 102010M (2017) https://doi.org/10.1117/12.2264744
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

We consider the task of estimating the scattering coefficients and locations of the scattering centers that exhibit limited azimuthal persistence for a wide-angle synthetic aperture radar (SAR) sensor operating in spotlight mode. We exploit the sparsity of the scattering centers in the spatial domain as well as the slow-varying structure of the scattering coefficients in the azimuth domain to solve the ill-posed linear inverse problem. Furthermore, we utilize this recovered model as a template for the task of target recognition and pose estimation. We also investigate the effects of missing pulses in the initial recovery step of the model on the performance of the proposed method for target recognition. We empirically establish that the recovered model can be used to estimate the target class and pose simultaneously for the case of missing measurements.

Conference Presentation

Citation Download Citation

Nithin Sugavanam and Emre Ertin "Limited persistence models for SAR automatic target recognition", Proc. SPIE 10201, Algorithms for Synthetic Aperture Radar Imagery XXIV, 102010M (28 April 2017); https://doi.org/10.1117/12.2264744

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