ISAR imaging using parametric L0-norm minimization

We present a sparsity-driven algorithm of inverse synthetic aperture radar (ISAR) imaging. 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 parametric L
₀
-norm minimization, which ensures the sparsest ISAR image.