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航天器自主导航状态估计方法研究综述

发布日期: 2021-06-10 | 浏览次数: 353
航天器自主导航状态估计方法研究综述

王大轶1, 侯博文1,2, 王炯琦2, 葛东明1, 李茂登3, 徐超3, 周海银2                          

1. 北京空间飞行器总体设计部, 北京 100094;
2. 国防科技大学, 文理学院, 长沙 410073;
3. 北京控制工程研究所, 北京, 100094


State estimation method for spacecraft autonomous navigation: Review

WANG Dayi1, HOU Bowen1,2, WANG Jiongqi2, GE Dongming1, LI Maodeng3, XU Chao3, ZHOU Haiyin2        

1. Beijing Institute of Spacecraft System Engineering, Beijing 100094, China;
2. College of Liberal Arts and Sciences, National University of Defense Technology, Changsha 410073, China;
3. Beijing Institute of Control Engineering, Beijing 100094, China

                                                    

摘要: 自主导航是航天器自主运行的核心关键技术。状态估计是实现航天器自主导航的核心手段,是指实时确定航天器在轨位置、速度和姿态等导航参数,是航天器自主导航技术的重点发展方向之一。首先,针对航天器自主导航的实际需求,阐述了研究航天器自主导航状态估计方法的必要性,具体从导航系统可观测性分析、导航滤波算法、导航系统误差补偿3个方面介绍了航天器自主导航状态估计方法的研究现状;然后,分析并总结状态估计方法在航天器自主导航系统中的实际应用;最后,结合理论研究和实际应用,给出了状态估计方法目前存在的主要问题并对其后续发展进行了展望。

关键词: 航天器, 自主导航, 状态估计, 可观测性分析, 导航滤波算法, 系统误差补偿

Abstract: Autonomous navigation is the key technology of spacecraft autonomous operation, while state estimation, the core means of spacecraft autonomous navigation which refers to the real-time determination of spacecraft orbit position, velocity, attitude and other navigation parameters, is one of the key development directions of the spacecraft autonomous navigation technology. Aiming at the practical requirements of the spacecraft autonomous navigation, this paper illustrates the necessity of studying spacecraft autonomous navigation state estimation method and introduces its research status from three aspects, including observability analysis of the navigation system, the navigation filtering algorithm, and error compensation of the navigation system. Then practical applications of the state estimation method in the spacecraft autonomous navigation system is analyzed and summarized. Finally, based on theoretical research and practical applications, the main problems of the state estimation method are presented and the future developments are prospected.

Key words: spacecraft, autonomous navigation, state estimation, observability analysis, navigation filter algorithms, system error compensation

                                                    


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