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为了提高月球软着陆过程的导航精度,嫦娥三号着陆器需要在动力下降前进行在轨陀螺安装、刻度因子和常值漂移标定.根据这一特定任务需求,设计了一种新颖的两层滤波算法.第一层滤波算法为惯性姿态估计,用于获得较为准确的星体角速度估值;第二层算法进行陀螺在轨标定,器载计算机使用第一层算法提供的星体角速度估值,利用UD分解扩展卡尔曼滤波,同时估计出陀螺的安装偏差、刻度因子误差和常值漂移.为了提高可观性,着陆器需要按照事先规划的角速度序列进行姿态机动.本文详细介绍了这一方法的原理和设计思路,并进行了公式推导和可观性分析.最后,结合实际飞行数据对该算法的效果进行了说明.
In order to improve the navigation accuracy of the lunar soft landing, the Chang’e III lander needs to calibrate the on-orbit gyro, scale factor and constant drift before the power descent.A novel two-layer filter Algorithm.The first layer of filtering algorithm is the inertial attitude estimation, which is used to obtain more accurate angular velocity estimation of the astral. The second layer algorithm is used to calibrate the gyroscope on-orbit. The onboard computer uses the first layer algorithm to provide the angular velocity estimation. Decomposition emanative Kalman filter, at the same time to estimate the gyroscope installation error, scale factor error and constant drift.In order to improve the observability, the lander needs to be in accordance with the pre-programmed angular velocity sequence of attitude maneuver.This paper describes in detail the principle of this method and Design ideas, and formula derivation and observability analysis.Finally, combined with the actual flight data to illustrate the effectiveness of the algorithm.