基于星敏感器的卫星姿态估计方法研究

Research on Satellite Attitude Estimation Based on Star Sensor

关键词:  星敏感器  自适应卡尔曼滤波  强跟踪卡尔曼滤波

Key words:  Star sensor  Adaptive Kalman filtering  Strong tracking Kalman filtering

摘要:

以星敏感器姿态信息作为测量数据,结合卫星姿态动力学方程组,采用增广卡尔曼滤波方法对无陀螺卫星姿态进行估计。研究发现,干扰力矩的变化会降低卫星姿态估计结果的精度,为此提出两种改进的姿态估计算法:增广自适应卡尔曼滤波方法和增广强跟踪卡尔曼滤波方法;仿真表明,两种算法都能很好地克服干扰力矩变化导致的精度下降现象。

Abstract:

This paper adopts the method of augmented extended Kalman filtering to estimate the attitude of a gyro-free satellite,using star sensor attitude information as metrics and combined with satellite attitude dynamics equations. Research shows that the variation of the disturbance torque can reduce the accuracy of the satellite attitude estimation. Two improved attitude estimation algorithms,augmented adaptive extended Kalman filtering and augmented strong tracking extended Kalman filtering,are proposed in this paper. Simulation results show that both of these algorithms can suppress the precision decrease caused by the disturbing torque variation.