ISAR imaging with sparse stepped frequency waveforms via matrix completion

Abstract

ABSTRACTCompressive sensing (CS) has been introduced into inverse synthetic aperture radar (ISAR) imaging with sparse stepped frequency waveforms (SSFWs). However, the performance of CS-based method decreases obviously for complex targets imaging in practice due to the CS-induced irregular range cell migration (IRCM) problem in the recovered high-resolution range profiles (HRRPs). In this letter, a novel method based on matrix completion (MC) theory is proposed for ISAR imaging with SSFWs. By reshaping the sparse stepped frequency echo into a Hankel matrix form, the full frequency signal can be recovered via MC algorithms. Thus, HRRPs without IRCM will be produced and an improved ISAR image will be obtained. The simulated results with real data demonstrate the validity of the proposed method.