A CA-NCS algorithm in curve trajectory for smart global village

Abstract

The development of embedded system makes it convenient to process SAR data in curve trajectory which caused by maneuvers with acceleration. To eliminate the effect of acceleration on imaging, a constant acceleration nonlinear chirp scaling (CA-NCS) algorithm in curve trajectory based on motion compensation is proposed. Through dividing the acceleration into forward-looking and cross-track acceleration, which could be divided into the acceleration vertical to the imaging plane and the other one in imaging plane further, we use vectorial methods to compensate the phase errors caused by acceleration. Moreover, for range migration we compensate it through NCS approach based on the accurate 2-D spectrum acquired by the method of series reversion (MSR). The system integrated with this algorithm can process SAR data in curve trajectory and reduce computation burden. In addition, the integration of the research in this paper and the machine learning will further identify the motion curve of the aircraft with cross-track acceleration quickly, and real-time SAR imaging can be realized which helps to achieve fast target localization in smart global village.