Computer Science – Information Theory
Scientific paper
2012-02-23
Computer Science
Information Theory
submitted to IEEE Transactions on Aerospace and Electronic Systems
Scientific paper
A sparsity-driven algorithm of inverse synthetic aperture radar (ISAR) imaging is proposed. Based on the parametric sparse representation of the received ISAR signal, the problem of ISAR image formation is converted into the joint estimation of the target rotation rate and the sparse power distribution in the spatial domain. This goal is achieved by sequential minimization of L0 and L2 norms, which ensure the sparsest ISAR image and the minimum recovery error, respectively.
Li Gaojun
Rao Wei
Wang Xiqin
Xia Xiang-Gen
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