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Sparse Representation For The Isar Image Reconstruction, Mengqi Hu
Sparse Representation For The Isar Image Reconstruction, Mengqi Hu
Theses and Dissertations
In this paper, a sparse representation for the data form a multi-input multi-output based inverse synthetic aperture radar (ISAR) system is derived for two dimensions. The proposed sparse representation motivates the use a of a Convex Optimization directly that recovers the image without the loss information of the image with far less samples that that is required by Nyquist–Shannon sampling theorem, which increases the efficiency and decrease the cost of calculation in radar imaging.