Attitude Estimation and Geometry Inversion of Satellite Based on Oriented Object Detection
Pengfei Xie, Lei Zhang, Yan Ma, Yejian Zhou, Xiaoqing Wang
Abstract
Retrieval of attitude and geometry of satellite targets from inverse synthetic aperture radar (ISAR) images is an important but difficult task, because of the complex scattering phenomenon and motion-dependent projection mechanism. In this letter, we construct a novel component extraction network (CEN)-based oriented object detection to obtain the projection parameters of the target components from ISAR images, then combine this CEN with particle swarm optimization (PSO) algorithm to retrieve the 3-D attitude and geometry of the target components. This proposed method can be used to accurately estimate the attitude and geometry of the target. The simulation experiments show the effectiveness and superiority of this method.