Parameter inversion algorithm of CSAR moving target based on PFA sub‐aperture images

Abstract

Circular SAR (CSAR) as a new kind of SAR imaging mode has the advantage of long-time observation. For the moving target, the corresponding parameters of the moving target can be calculated by using the position information from the apparent coordinates of the moving target in these CSAR sub-aperture images. The CSAR sub-aperture imaging algorithms include BP and PFA, and the existing parameter estimation model is established on those well-focused and localised images. However, they account for a substantial computation. Here, an improved algorithm for parameter estimation based on CSAR sub-aperture images obtained by PFA is proposed. The wave-front phase error compensation is abandoned, and a new parameter estimation model is established based on PFA images with geometric positioning error. The computational complexity of the whole process of the algorithm is reduced, and the practicability is improved. The point target simulation shows that the method is effective and accurate.