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复杂环境下航天器姿态确定系统存在系统参数不确定性,并且可能存在观测数据的间断丢失情况.对此,本文研究了一种新的鲁棒滤波算法.该算法采用线性预测子系统重构补偿丢失的观测信号,并利用其参与到测量更新阶段,采用极小极大理论推导出具有观测数据丢失的不确定性系统的鲁棒状态估计的递推形式.将该方法用于复杂环境下的航天器姿态确定系统中,通过仿真验证了算法的有效性.
In the complex environment, the spacecraft attitude determination system has the uncertainty of the system parameters, and there may be intermittent loss of the observed data.In this paper, a new robust filtering algorithm is studied in this paper, which uses linear prediction subsystem to reconstruct the compensation And use it to participate in the phase of measurement and updating, the recursive form of the robust state estimation for uncertain systems with observed data loss is derived using the minimax theory.This method is applied to the complex environment In spacecraft attitude determination system, the effectiveness of the algorithm is verified through simulation.