A Novel CFFBP Algorithm With Noninterpolation Image Merging for Bistatic Forward-Looking SAR Focusing
Yachao Li, Gaotian Xu, Song Zhou, Mengdao Xing, Xuan Song
Abstract
Fast factorized back-projection (FFBP) has significant advantages for bistatic forward-looking synthetic aperture radar (BFSAR) imaging with arbitrary geometry and complex configuration. Conventional FFBP is generally based on the polar coordinate system (PCS) for recursive processing; however, it involves huge interpolations and causes computational inefficiency. In this article, a novel FFBP is developed for BFSAR focusing based on the Cartesian coordinate system (CCS), which is referred to as Cartesian fast factorized back-projection (CFFBP). In the new algorithm, a two-step spectrum correction is designed to avoid spectrum aliasing, and the Nyquist sampling requirement (NSR) for the BFSAR image spectrum can be decreased significantly. With low NSR in CCS, subimage merging can be implemented with noninterpolation processing, so that the proposed algorithm can achieve high performance in both accuracy and efficiency. Moreover, the practical problem of motion error is particularly considered in algorithm development, and well-adapted data-driven motion compensation (DDMC) is integrated with CFFBP based on which a new Cartesian fast time-domain (CFTD) processing framework is developed for BFSAR application. Promising results from both simulation and raw data experiments are provided and analyzed to validate the high performance of the proposed algorithm.