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最优线性姿态估计算法以罗格里斯参数作为姿态描述,具有计算量小、精度高等优点。但它是一种基于单点信息的估计算法。提出一种递归思想,整合当前时刻以及历史时刻的多点测量信息,根据最优判定函数建立不同时间节点上测量数据间的数学模型关系,对单点算法中的关键元素M和z进行迭代设计,并由此推导出一种新的递归姿态估计算法。仿真结果表明,最优递归线性姿态估计算法在航天器稳定慢速机动的情况下,解算精度要显著优于单点的最优线性姿态估计算法。
The optimal linear pose estimation algorithm using the Roger’s parameters as the pose description has the advantages of small calculation amount and high precision. But it is based on a single point of information estimation algorithm. A new idea of recursion was proposed to integrate the multi-point measurement information of the current time and the historical time. According to the optimal decision function, the relationship between the mathematical models of the measured data at different time nodes was established. The key elements M and z in the single-point algorithm were iteratively designed , And derive a new recursive attitude estimation algorithm. The simulation results show that the optimal recursive linear attitude estimation algorithm is significantly better than the single point optimal linear attitude estimation algorithm when the spacecraft is stable and slow maneuvering.