Phase Compensation and Image Autofocusing for Randomized Stepped Frequency ISAR

Randomized stepped frequency (RSF) waveforms are attractive for inverse synthetic aperture radar (ISAR) imaging due to their synthetic-bandwidth system architecture and outstanding electronic counter-countermeasure characteristics. However, the extra complexities of the RSF radar's frequency oscillator and the target echo model make phase compensation and image autofocusing more complicated. In this paper, we introduce a novel method for the phase compensation and image autofocusing of RSF-ISAR. The new method consists of the following two stages: the first is a parametric coarse compensation for target radial motion, and the second is a non-parametric fine compensation for motion residuals and radar system imperfection. Two target models, a naive target consisting of unit point scatterers and a Yak-42 target obtained from field experiments, are used for numerical analysis, which shows the effectiveness and superiority of the proposed method.