多传感器滤波融合的惯性定位算法

发布时间：2018-01-09 01:03

本文关键词：多传感器滤波融合的惯性定位算法　出处：《电子技术应用》2017年10期 　论文类型：期刊论文

【摘要】：针对在导航系统姿态解算中,陀螺仪和电子罗盘在解算姿态时分别存在积分误差和磁场干扰的问题,提出了利用Kalman滤波和互补滤波相融合的算法进行定位。首先将电子罗盘和陀螺仪通过Kalman滤波得出最优估计四元数,然后利用互补滤波算法对陀螺仪的漂移进行补偿得到校正后的四元数,将此次得到的四元数和Kalman滤波得出最优估计四元数再次通过Kalman滤波对四元数进行第二次最优估计,进而输出姿态角。实验中对比了本算法和互补滤波算法、无滤波算法的效果。实验证明,该算法不仅可以有效解决方位角误差发散问题,还有效解决了磁场干扰问题,实现了高精度的方位输出。
[Abstract]:In the attitude calculation of the navigation system, the gyroscope and the electronic compass have the problems of integral error and magnetic field interference respectively in the attitude calculation of the navigation system. An algorithm combining Kalman filter and complementary filter is proposed. First, the electronic compass and gyroscope are filtered by Kalman to get the optimal estimated quaternion. Then complementary filtering algorithm is used to compensate the drift of gyroscope to get the corrected quaternion. The quaternion and Kalman filter are used to obtain the optimal estimate quaternion. The second optimal estimation of quaternion is carried out by Kalman filter. The experimental results show that this algorithm can not only solve the problem of azimuth error divergence effectively, but also can solve the problem of azimuth error divergence. It also effectively solves the problem of magnetic field interference and achieves high precision azimuth output.
【作者单位】：河北工业大学电子信息工程学院;
【分类号】：TN96;TP212
【正文快照】： 0引言面对这些问题,本文提出了一种Kalman滤波和互补滤波随着以MEMS(Micro-electromechanical Systems)传感器融合的惯性定位算法,该算法在设计Kalman滤波中,将为代表的微型化惯性器件的发展,基于捷联式惯导原理加速度计和磁强计融合得出的四元数作为观测值,利用和MEMS传感器

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