多姿态敏感器测量的信息融合定姿方法研究

Research on Information Fusion Method for Satellite Attitude Determination Based on Multi-Sensor Measurement

基于最优融合估计理论,给出并证明了多敏感器组合姿态确定系统状态最优融合估计形式。设计了基于信息分配的多信息融合联合滤波器结构和算法,分析估计性能,讨论了决定联合滤波器融合的性能信息分配因子选择方法,提出了一种基于协方差阵特征值平方分解的动态自适应信息分配因子确定方法。以某卫星多姿态敏感器组合测量为例,推导了卫星姿态确定的误差状态方程和各子系统的量测方程及观测阵。仿真结果表明:采用联合滤波器对多敏感器卫星姿态确定系统进行信息融合能改善定姿精度,有效抑制滤波发散,并提高整个系统的运算与收敛速度。

Based on optimal fusion estimation,the expression of state optimal fusion estimation in satellite multi-sensor attitude systems was given and proved in this paper.The structure and algorithm of federal Kalamn filter（FKF） for multi-information fusion based on information allocation principle were designed,and the estimation performance was also analyzed.The determination method of the information allocation factor which would affect the performance of the FKF was discussed.The self-adaptively determination method of the information allocation factor based on the eigenvalue square decomposition of the covariance matrix was put forward.The measurement equation of each sub-system,and the measurement matrix in satellite attitude determination system were deduced for some satellite integrated attitude determination system.The simulation results showed that the accuracy and stability would be improved and the divergence was suppressed by adopting FKF to take information fusion for estimating satellite attitude based on multi-sensor measurement,and the operational speed and convergence speed of the whole system were enhanced more.