Large-Scene Polar Format Algorithm for Circular SAR Subaperture Imaging

Abstract

Circular synthetic aperture radar (CSAR) is an advanced mechanism with the capability of three-dimensional imaging, which can continuously observe the omnidirectional scattering characteristic of the ground scene. The time-domain imaging algorithm with accurate focusing ability, such as the back-projection algorithm, is often used in large-scene CSAR imaging. Due to a large amount of echo data, time-domain imaging algorithms are typically time-consuming. The polar format algorithm (PFA) is a convenient and efficient frequency-domain imaging algorithm. However, the azimuth defocus caused by the phase error of wavefront curvature limits the depth of focus in CSAR images formed by PFA. In this article, we propose a large-scene PFA (LS-PFA) for CSAR sub-aperture imaging with space-variant post-filtering. By leveraging the phase error of wavefront curvature for arbitrary curved flight paths, a space-variant filter suitable for the large-scene subaperture CSAR image formed by PFA is designed to compensate for the azimuth defocus. LS-PFA provides an efficient and general solution to acquire well-focused large-scene subaperture CSAR images under arbitrary curved flight paths. The focusing performance of LS-PFA is verified with simulation and experimental results.