摘要
研究了绕月卫星自主导航方法,提出了由星敏感器、紫外月球敏感器和测高仪组成的多源信息组合导航方案。将Unscented Kalman滤波(UKF)应用于非线性导航系统,采用信息融合技术设计了相关的联邦滤波算法,实现了系统的信息互补,完成了卫星轨道的最优估计。利用数学仿真对这种导航系统的有效性进行了验证,并与基于扩展Kal man滤波(EKF)的信息融合算法进行了比较。仿真结果表明,所提出的UKF融合算法具有良好的稳定性,可进一步提高导航系统的精度。
We propose a multi-source information autonomous navigation scheme, which composes of star sensor, ultraviolet moon sensor and the altimeter for satellite around Moon. Unscented Kalman filtering（UKF） is used in nonlinear systems. The optimal orbit of the satellite is determined by a federated Kalman filter which realizes information comple- ment based on a new information fusion algorithm. We also compared with the extend Kal- man filtering（EKF） based on information fusion. The effectiveness of the navigation scheme was implemented by numerical simulations. The simulation results show that UKF informa- tion fusion algorithm can improve the navigation precision and reliabilities.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2010年第3期257-260,共4页
Geomatics and Information Science of Wuhan University
基金
国家杰出青年科学基金资助项目(40625013)
国家863计划资助项目(2007AA12Z311)
国家自然科学基金资助项目(40890160)
关键词
月球卫星
自主导航
UKF
信息融合
lunar satellite
autonomous navigation
UKF
information fusion
