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The compressive sensing (CS) has been successfully used in inverse synthetic aperture radar (ISAR) imaging. Since the sparse reconstruction based on l1 norm is sensitive to the regularized factor and makes it inconvenient to be used in practice, the sparse Bayesian learning (SBL) is considered in this situation, which retains a preferable property of the l0 norm and has no user parameter. In this...
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