一种基于卡尔曼滤波的姿态信息融合方法

Kalman filtering-based attitude information fusion method

针对卫星平台上存在的由高频微角颤振引起的载荷光轴指向精度降低,提出了一种基于卡尔曼滤波的姿态信息融合方法,提高姿态确定指向精度。建立基于星敏感器与陀螺的低频带姿态确定系统和MHD-ARS(magneto-hydro-dynamics,MHD,angular-rate-sensor,ARS)高频姿态信息测量系统的数学模型,采用卡尔曼滤波进行宽带宽的姿态信息融合。仿真结果分析表明当存在高频微角颤振时,采用卡尔曼滤波的姿态信息融合方法的估计精度要优于传统的低频带姿态确定系统,且在频域上能够实现扩展姿态测量带宽的目的,验证了姿态信息融合方法的有效性和精确性。

The high-frequency angular microvibration of satellite platform results in the decrease of optical-axis pointing accuracy, a Kalman filtering-based attitude information fusion method is presented, thus improving the pointing accuracy of attitude determination. The mathematical models of the system combined with gyro, star sensor and MHD-ARS are built, and the Kalman filter is used to realize the high-bandwidth attitude information fusion. The simulation results indicate that the estimated accuracy of Kalman filtering attitude information fusion method is better than conventional system of low frequency sensor. Accordingly, the attitude information fusion method is verified to be efficient and accurate.