4 May 2016 Sparse representation for the ISAR image reconstruction
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Abstract
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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