4 May 2016 Sparse representation for the ISAR image reconstruction
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In this paper, a sparse representation of the data for an inverse synthetic aperture radar (ISAR) system is provided in two dimensions. The proposed sparse representation motivates the use a of a Convex Optimization that recovers the image with far less samples, which is required by Nyquist-Shannon sampling theorem to increases the efficiency and decrease the cost of calculation in radar imaging.
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Mengqi Hu, Mengqi Hu, John Montalbo, John Montalbo, Shuxia Li, Shuxia Li, Ligang Sun, Ligang Sun, Zhijun G. Qiao, Zhijun G. Qiao, "Sparse representation for the ISAR image reconstruction", Proc. SPIE 9857, Compressive Sensing V: From Diverse Modalities to Big Data Analytics, 98570B (4 May 2016); doi: 10.1117/12.2228095; https://doi.org/10.1117/12.2228095

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