ISAR imaging with sparse stepped frequency waveforms via matrix completion

ABSTRACT

Compressive 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.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant number 61372166, 61571459; the Natural Science Basic Research Plan in Shaanxi Province of China under Grant number 2014JM8308.