Improved EANLCS Algorithm Based on “Non-Stop-Go” Model for Bistatic SAR Imaging With GEO Transmitter and High Maneuvering Platform Receiver

Abstract

The geosynchronous Earth orbit-high maneuvering platform bistatic synthetic aperture radar (GEO-HMP BiSAR) system uses a geosynchronous Earth orbit (GEO) satellite as the transmitter and a high maneuvering platform as the receiver. It offers advantages such as the wide coverage, short revisit periods, multiangle observation, and flexible configuration, which has the ability of the high-resolution imaging and detection. However, the high maneuvering platform and the requirement of the high resolution render the conventional “stop-go” assumption invalid. Moreover, severe range-azimuth coupling of echo signals under the large-scale heterogeneous space conditions poses the significant challenges in the high-precision GEO-HMP bistatic synthetic aperture radar (BiSAR) imaging. To address these issues, an improved extended azimuth nonlinear chirp scaling (NLCS) algorithm based on the “non-stop-go” model for the GEO-HMP BiSAR imaging is proposed. First, considering the longer signal transmission delay and the higher mobility of the receiver platform in the GEO-HMP BiSAR system, an improved “non-stop-go” model suitable for the GEO-HMP BiSAR imaging is provided, which can prevent the defocused imaging caused by the consideration of the platform’s motion during the pulse duration. Second, to tackle the problem of the severe range-azimuth coupling under large-scale heterogeneous conditions, an improved extended azimuth NLCS (EANLCS) algorithm for the GEO-HMP BiSAR imaging is presented. In the range processing, the linear range cell migration (RCM) correction is first performed to eliminate the linear RCM, and then an improved residual RCM correction (RRCMC) filter is applied to remove the residual RCM. This addresses the limitations of the traditional NLCS algorithm which fail to account for the acceleration and jerk (the derivative of acceleration). In the azimuth processing, a prefiltering step is first adopted to simplify the radar signal, and a new perturbation function is then presented to equalize the azimuth frequency modulation rate, finally, an azimuth compression filter is used to achieve the focused imaging. Experimental results tested on both simulation and measured BiSAR data validate the correctness and effectiveness of the proposed signal model and imaging method.