一种采用衰减记忆滤波的环月航天器自主导航方法研究

Autonomous Deep Space Navigation Based On Fading Memory Filtering

针对环绕月球运行的深空探测航天器提出了一种新的自主导航方案,该方案是以两个环月航天器之间的相对位置矢量信息作为量测量,结合轨道动力学方程,对航天器的轨道自主估计确定,方案中考虑了符合实际的复杂摄动影响,并对描述动力学特性的数学模型与噪声的统计模型不准确而导致的滤波发散问题,提出利用一种经过衰减记忆改进的平方根非线性滤波(SRUKF)算法进行解决。对所提方案做了大量的计算机仿真,同时详尽的分析和比较了由于衰减因子及采样周期变化所带来的影响。从仿真结果上看,衰减记忆滤波处理能够很好得抑制非线性状态转移条件下的滤波发散趋势。

A new navigation Scenario had been designed and analyzed to autonomously determinate the orbits of two spacecrafts when they are circling the moon, based on measurements of the relative positions vector from one spacecraft to the other. In this article, more realistic and complex orbital perturbation factors had been considered, which would cause a divergent result due to the crrors in the model of dynamics and process noises. Accordingly, a reformative square-root Uneented Kalman filtering （SRUKF） based on fading memory method was proposed, which was able to resolve this divergent problem in a good condition. Viewed from the simulation results, the new estimated arithmetic performs well as that was expected.