基于鲁棒卡尔曼滤波的编队卫星相对导航

Relative Navigation for Spacecraft Formation Flying Based on Robust Kalman Filter

为提高编队卫星相对导航精度和计算稳定性,采用鲁棒卡尔曼滤波进行相对位置和相对速度的估计。对星间相对动力学方程进行适应性改造,使其具有线性离散不确定性系统形式。以载波相位差分GPS为观测模型,采用鲁棒卡尔曼滤波进行相对状态估计。数值仿真结果表明,该算法相对于扩展卡尔曼滤波算法具有明显优势,导航精度更高、鲁棒性更强,具有一定的工程应用价值。

Aiming at improving the stability and computation precision of the relative navigation of formation flying satellites, a robust Kalman filter （RKF） is presented for the estimation of relative position and velocity. The dynamics equations of relation motion among satellites are modified to a discrete linear system with uncertainty. Based on the observation model of carrier phase differential GPS, the relative states are estimated by using RKF. The algorithm takes obvious advantages than EKF including higher navigation precision and stronger robustness. The simulation results indicate that the relative navigation is effective in practical applications by using RKF.