Parametric Curved-Surface Imaging Algorithm for Space Target ISAR Imaging With Rotating Component

Abstract

Residual range migration hinders high-resolution inverse synthetic aperture radar (ISAR) imaging of space targets when traditional migration through resolution cell (MTRC) correction algorithms is applied, particularly for rotating components that continuously change their attitude relative to the main body. To address this issue, we propose a parametric curved-surface imaging algorithm (PCSIA) for space target ISAR imaging. PCSIA significantly reduces residual range migration by decomposing the 2-D interpolation of the curved surface into two nonlinear 1-D interpolations, enabling a clearer analysis of the residual migration. In addition, we introduce a parametric refocusing method specifically designed for imaging the blurry scatterers on the rotating component. This method describes the azimuthal blur of scatterers on the rotating component, which is caused by parameter mismatch. It also aids in identifying scatterers on the main body, as they are well focused in azimuth after applying PCSIA. Following the application of scatterer CLEAN on the main body, the 1-D range profiles of the rotating component are restored through parametric inverse interpolation, enabling secondary refocusing of scatterers on the rotating component. Simulations demonstrate that PCSIA significantly improves MTRC compensation, and ISAR images obtained through the parametric refocusing method aligns well with theoretical expectations.