A Generalized Phase Gradient Autofocus Algorithm

摘要

The phase gradient autofocus (PGA) algorithm has seen widespread use and success within the synthetic aperture radar (SAR) imaging community. However, its use and success has largely been limited to collection geometries where either the polar format algorithm (PFA) or range migration algorithm is suitable for SAR image formation. In this paper, a generalized phase gradient autofocus (GPGA) algorithm is developed that is applicable with both the PFA and backprojection algorithm (BPA), thereby directly supporting a wide range of collection geometries and SAR imaging modalities. The GPGA algorithm is shown to preserve the four crucial signal processing steps comprising the PGA algorithm while alleviating the constraint of using a single scatterer per range cut for phase error estimation, which exists with the PGA algorithm. Moreover, the GPGA algorithm, whether using the PFA or BPA, is shown to yield an approximate maximum marginal likelihood estimate of phase errors having marginalized over unknown complex-valued reflectivities of selected scatterers. Simulation and experimental results produced by applying the GPGA algorithm to PFA and BPA SAR images are presented.