基于平方根差分滤波的动中通姿态稳定方法

Square-Root Central Difference Kalman Filter for Attitude Stabilization in Satcom On-The-Move

为了隔离载体扰动对天线指向的影响,研究了单基线GPS和微惯性传感器组合的低成本姿态估计及稳定方法。该方法以四元素和陀螺误差作为状态变量,根据陀螺角速率信息、加速度计的重力场信息和单基线GPS航向信息分别建立状态方程和量测方程,设计具有不同测量周期的平方根差分滤波分别融合惯性传感器和GPS信息,解决了加速度计与单基线GPS航向信息输出频率不一致问题;利用估计出的姿态角在角位置环路上对天线进行捷联稳定,隔离载体扰动。仿真结果表明,平方根差分滤波能有效估计出载体姿态,利用中等精度的微惯性器件可以满足动中通姿态稳定的需求。

In order to isolate the antenna pointing from disturbance of vehicle, an attitude estimation and stabilization method based on the MEMS inertial sensors and single baseline GPS was studied. Taking the quaternion and gyroscope drifts as state variables, the state equation and measurement equation were built up respectively according to the angular output of gyroscopes, the gravity output of accelerometers and the heading attitude information derived from GPS. Considering the different output frequency between accelerometers and GPS, a Square-Root Central Difference Kalman Filter （SRCDKF） containing two measurement equations with different update frequencies was designed. Then, a strap-down stabilization method for angular position was used to isolate disturbance of vehicle with the estimated attitude information. The results show that SRCDKF achieves good estimation accuracy,which can meet the demand for the attitude stabilization of mobile communication.