基于联邦UKF算法的月球探测器自主组合导航

研究了月球探测器在地一月转移轨道阶段的自主导航方法，提出了利用地月位置信息和星光角距测量信息实现探测器自主组合导航的方案。针对导航系统的状态方程非线性的特点，将Unscented卡尔曼滤波算法和信息融合技术相结合，设计了新的联邦滤波器并应用于自主导航系统中。对这种导航方案进行了数值仿真，和传统的联邦滤波算法进行了比较。仿真结果表明，所提出的组合导航方法和联邦滤波算法的导航位置估计精度约为1km，速度估计精度约为0．01m／s，并且具有良好的鲁棒性和容错性能。

Autonomous Integrated Navigation for Lunar Probe Based on Federated UKF Algorithm

This paper studies an approach of autonomous navigation for lunar probe on the earth-moon transfer trajectory.A new scheme for lunar probe's autonomous integrated navigation which uses the observed information of the earth-moon position and the starlight angular distance is proposed.In order to solve the nonlinear problem of the state equations,an improved federated filtering based on Unscented Kalman filtering and information fusion is designed and used in the navigation system.The numerical simulation for this navigation scheme is implemented and compared with the traditional federated filtering.Results show that navigation position accuracy is about 1km,and the velocity accuracy is about 0.01m/s.The results demonstrate that the autonomous integrated navigation method and the new federated filtering can improve the navigation precision,robustness and reliability.