基于二阶插值滤波的室内航向估计算法研究

在室内行人导航中,为获取精确的航向角,提出了一种基于二阶插值滤波的航向估计算法。该算法通过建立四元数姿态运动测量模型,采用二阶插值滤波对陀螺仪、加速计和磁强计的测量数据进行数据融合,实现航向角解算,以过程噪声和测量噪声为设计参数,构造自适应噪声协方差矩阵,实现协方差误差估计最小化。通过对行走长方形参考路径得到的数据进行处理,加速计和磁强计组合与陀螺仪航向估计算法动态误差分别为13.6°和6.9°,采用二阶插值滤波航向估计算法后动态误差为2.3°。实验结果表明,该算法有效提高了航向估计的精度,减小了陀螺仪漂移、载体的线性加速度和周围局部磁场干扰对航向估计的影响。

Study on A Heading Estimation Algorithm Based on Second-order Divided Difference Filter

A heading estimation algorithm based on second order divided difference filter (DDF2) was presented to obtain the high accuracy of the heading angle in the indoor pedestrian navigation. Through establishing a quaternion attitude movement measurement model, the heading angle calculation was realized by using the DDF2 to fusion the measured data of the gyroscope, accelerometer and magnetometer. By using the process noise and measurement noise as the design parameters, the adaptive noise covariance matrix is constructed to minimize the covariance error estimation. By processing the data obtained from the rectangular reference path, the dynamic errors from the combination of accelerometer and magnetometer as well as the gyro heading estimation algorithm were 13.6°, 6.9° respectively, while the dynamic error was 2.3° after DDF2 heading estimation algorithm was used. The experimental results showed that the proposed algorithm has effectively improved the accuracy of heading estimation, reduced the effects of gyroscope drift, the linear acceleration of the vehicle and the local magnetic disturbance on the heading estimation.