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针对利用地球重力场和磁场矢量观测进行自主姿态测量的姿态仪表现有算法的不足,提出了一种新的优化递推估计算法:采用卡尔曼滤波框架,利用加权统计线性回归技术进行测量更新,在相同条件下,可将测量精度提高一倍,并能同步提供姿态速率信息。仿真结果表明了该算法的有效性和合理性。
Aiming at the deficiency of the existing algorithms of the attitude instrument which uses the earth’s gravitational field and the magnetic vector observation to measure the autonomous attitude, a new optimized recursive estimation algorithm is proposed. The Kalman filter framework is used to measure and update using the weighted statistical linear regression technique, Under the same conditions, the measurement accuracy can be doubled and the attitude speed information can be provided synchronously. Simulation results show the effectiveness and rationality of this algorithm.