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针对重力卫星质心在轨标定问题,提出了一种将预测滤波与卡尔曼滤波相结合的标定算法。该算法首先利用磁力矩器产生一个明显大于干扰力矩的周期性力矩作用于卫星上,然后利用陀螺数据实现了卫星角加速度的预测滤波估计,并通过静电加速度计信息设计卡尔曼滤波器,实现卫星质心的标定;最后进行了数学仿真,仿真结果表明该算法针对卫星的角加速度及质心位置能够实时估计,三轴最佳标定精度分别为[0.062 8 0.032 4 0.041 4]mm,实现了卫星质心较为精确的标定。
Aiming at the problem of on-orbit calibration of gravity satellite centroid, a calibration algorithm combining predictive filtering with Kalman filtering is proposed. The algorithm firstly uses the magnetic torque generator to generate a periodic moment which is obviously greater than the disturbance torque and then uses the gyro data to realize the prediction filter estimation of the angular acceleration of the satellite. The Kalman filter is designed based on the information of the electrostatic accelerometer to realize the satellite Finally, a mathematical simulation is carried out. The simulation results show that the proposed algorithm can estimate the angular acceleration and centroid position of the satellite in real time, and the optimal calibration accuracy of the three axes are [0.062 8 0.032 4 0.041 4] mm, respectively. Precise calibration.