Dynamic Analysis of Spin Satellites Through the Quadratic Phase Estimation in Multiple-Station Radar Images
Yejian Zhou, Lei Zhang, Shaopeng Wei, Yunhe Cao
Abstract
Dynamic analysis of in-orbit satellites is of interest for space situation applications. Some exploratory methods have been presented to analyze the state of attitude-steadied satellites in the complex space situation, but effectively estimating the dynamic parameters of spinning satellites remains a significant and interesting challenge nowadays. With decoupling target spin estimation from its trajectory motion, this paper proposes a novel dynamic estimation approach by using multiple-station inverse synthetic aperture radar (ISAR) images. In brief, quadratic phase characteristic, which is usually regarded as a negative factor for ISAR imagery in conventional algorithms, is now directly exploited to build an explicit expression of the relative motion between the spin in-orbit satellite and radar. Then, based on the developed image refocusing algorithm, these phase coefficients are extracted from the multiple-station images and substituted into the optimization of target dynamic estimation. In the end, target dynamic parameters, including its instantaneous attitude vector and spin speed, are estimated through particle swarm optimization. Experiment results illustrate the feasibility of the proposed algorithm. To some degree, this work also reflects the advantages of multiple-station ISAR system in some space applications.