摘要
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应用问题,提出了一种新的最优递推估计算法。该算法采用卡尔曼滤波框架,利用加权统计线性回归并结合自适应滤波技术进行测量更新,与现有方法相比,在提高测量精度的同时,增加了同步提供姿态速率信息的功能。仿真结果表明,新算法的姿态估计精度比目前常用的直接计算方法提高近两倍。
A novel optimal attitude and attitude-rate estimation algorithm is proposed to address the problem of autonomous attitude determination using gravitational filed and geomagnetic field observation. The algorithm is in the Kalman filter framework and employs weighted statistical linear regression and adaptive filtering to finish the measurement update. It can synchronously provide attitude-rate information . The simulation results show that the algorithm can triple approximately the measurement precision of what the common method did.
出处
《航空学报》
EI
CAS
CSCD
北大核心
2005年第5期594-597,共4页
Acta Aeronautica et Astronautica Sinica
基金
军队武器装备科研(H1022003166)资助项目
关键词
导航
姿态测量
卡尔曼滤波
加权统计线性回归
自适应滤波
navigation
attitude determination
Kalman filtering
weighted statistical linear regression
adaptive filtering
