Abstract:

For existing algorithms are difficult to satisfy the applied requirements, a Bayesian estimation-based algorithm for geomagnetic aided inertial navigation is proposed for aerocraft navigation. The core idea is to convert position estimation to probability estimation. A position correction strategy is also provided in this algorithm. Simulation experiments were performed in which measured data were used. Results show that the algorithm has an average navigation accuracy of 89 meters and spend average 156 seconds for first correction the INS (inertial navigation system). In addition, the performance of the algorithm is not sensitivity to initial estimation errors.

Key words: Bayesian estimation, geomagnetic aided inertial navigation algorithm, probability estimation

摘要：

针对已有算法难以满足实际应用需求的问题, 提出一种面向飞行器导航的基于贝叶斯估计的地磁辅助惯性导航算法, 其核心思想是将估计区域网格化, 将位置估计转化为概率估计。该算法给出了位置修正策略。基于实测地磁数据的仿真实验结果显示, 在仿真条件下, 平均导航误差为89 m, 首次修正惯导的平均时间为156 s, 算法性能对初始估计误差的敏感性不显著。

关键词: 贝叶斯估计, 地磁辅助惯性导航算法, 概率估计