Inverse Synthetic Aperture Radar Imaging Via Modified Smoothed $L_{0}$ Norm

Compressive sensing theory is able to exactly recover an unknown sparse signal from observation samples with high probability. In this letter, we convert the imaging into a problem of signal reconstruction with the aid of orthogonal basis in the framework of high-resolution inverse synthetic aperture radar imaging. More specifically, we propose a new method based on smoothed L₀ norm, whose recovery rate is faster than the algorithm based on L₁ norm. Experiment results with real data show that our proposal is more efficient than the L₁ norm algorithm.