A Parameter-Adjusting Autoregistration Imaging Algorithm for Video Synthetic Aperture Radar

Abstract

Video synthetic aperture radar (ViSAR) is gaining increasing attention in the remote sensing area due to its advantages in continuous observation compared with conventional synthetic aperture radar (SAR). Generally, the polar format algorithm (PFA) is utilized to generate the ViSAR frames considering both processing efficiency and imaging quality. However, the changes in squint angles for different ViSAR frames will cause variations in target positions when the classic fixed-parameter PFA is utilized. Hence, an image registration step is typically needed, which greatly increases the computational load. Meanwhile, the azimuth resolution also deteriorates rapidly for the ViSAR frames as the squint angle becomes larger. In order to solve the aforementioned problems, a parameter-adjusting autoregistration PFA (PAAR-PFA) is proposed for the ViSAR. By adjusting system parameters, such as carrier frequency, pulsewidth, and sampling frequency, according to the azimuth sampling positions, PAAR-PFA can achieve autoregistration for ViSAR frames without range interpolation and geometric correction in fixed-parameter PFA, which significantly improves the processing efficiency. At the same time, since the azimuth sampling number of frame data is adjusted with the squint angle, the variation range of the azimuth resolution under different squint angles is considerably reduced. Point target and extended target simulations confirm the feasibility of the proposed algorithm.