一种星间相对状态估计方法

编队自主导航是实现分布式遥感系统星间协同观测的基础。为实现分布式遥感系统星间相对状态的精确确定，提出一种基于MEMS激光雷达与纳型星罗盘的星间相对状态估计方法。借助相对姿态、轨道运动学方程建立了星间相对状态的无迹卡尔曼滤波(UKF)算法，解决了MEMS激光雷达测量与参考航天器姿态耦合的问题，并利用预定入轨参数及高精度轨道外推(HPOP)对方法进行仿真校验。结果表明，该方法具有可行性和实用性，估计精度满足分布式遥感任务需求，能够较好解决中远距离星间相对状态估计问题。

A Relative State Estimation Approach for Spacecraft Formation Flying

Formation autonomous navigation is the basis for the collaborative observation of the distributed remote sensing formations. In order to realize the accurate determination of the relative state between the different spacecraft, a relative state estimation approach is proposed based on the MEMS LiDAR and nano star tracker. An unscented Kalman filter (UKF) is established based on the relative attitude and orbit kinematics equations. The coupling issue between the measurement of the MEMS LiDAR and the attitude of the reference spacecraft is solved. The high precision orbit propagator (HPOP) model is used in the simulations. The results show that the proposed method is feasible and practicable, and the accuracy of the estimation meets the needs of the distributed remote sensing tasks. It is a good candidate to solve the relative state estimation problem for long-and middle-distance formation.