基于日地月方位信息的月球卫星自主导航

采用自主导航技术，可以降低月球卫星的任务成本，提高其生存能力。现研究了利用太阳敏感器、地球敏感器和月球敏感器测量出的卫星-太阳、卫星-地球和卫星-月球方向矢量作为观测量，采用迭代最小二乘方法、定历元时刻的卫星状态，并以轨道预报的方式实现月球卫星的自主导航。对该自主导航算法进行了数学仿真，分析比较了敏感器精度、部分轨道参数等因素对定位精度的影响，总结了其变化规律。最后对比了迭代最小二乘方法与扩展卡尔曼滤波的导航仿真结果，结果表明前者具有更高的精度。

Autonomous Navigation for Lunar Satellite based on the Optical Information of Sun-Earth-Moon

Autonomous navigation technology can reduce the cost of missions and strengthen the survival ability of a lunar satellite. This paper dealt with autonomous navigation of a lunar satellite using the optical data that are, respectively, measured by the sun sensor, the earth sensor and the moon sensor. From those optical data and the ephemerides of the sun and the earth, the iterative least square (ILS) method was used to estimate the epoch state of the lunar satellite's orbit. With this epoch state, the orbit parameters for the future 24 hours were predicted. Simulation results of autonomous navigation of a certain pole orbit lunar satellite showed that the position error at epoch time was less than 40m. Furthermore, the effects of some orbit parameters and measurement accuracy of sensing devices on orbit determination precision were analyzed and compared. Finally, comparison between results of the ILS method and those of Extended Kalman Filter (EKF) showed that the former had the higher precision.