行人自主导航定位的多级滤波方法

Multi-stage Filtering Method for Pedestrian Navigation and Location

针对携带式IMU对行人进行导航定位时,惯性器件的误差随时间增长累积变大,影响导航准确性的问题,研究了一种多级滤波的方法:零速检测并利用扩展卡尔曼滤波进行零速校正后,再通过室内几何布局特征划分矢量区,利用投影匹配算法判定位置的最优解,来确定人行走轨迹。用自主研制的MIMU行人导航模块做了场地实验,结果表明:该方法相对目前单级卡尔曼滤波的惯性导航方法,能够很好地抑制惯性导航误差积累,且不会出现行人轨迹穿墙问题,定位精度为0.9%,具有理论和实际的意义。

In the process of navigation and location of a pedestrian for a wearable IMU,the inertial device generates an accumulated drift error affecting the navigation and location accuracy of pedestrian navigation. A multi-stage filtering method is studied:after the zero-speed detection and the zero-speed correction based on Extended Kalman Filter are carried out,the vector domain is divided by the indoor geometric layout features,and the projected matching model is used to determine the optimal coordinates of the nodes to get the trajectory.Using the self-developed MIMU pedestrian navigation module,a field experiment was conducted.The experimental results show that this method can suppress the accumulation of inertial navigation error,which is better than the current single-stage Kalman filter inertial navigation method.There is no pedestrian trajectory passing through the wall.The navigation and location accuracy of pedestrian navigation is improved and the location accuracy is 0.9%.The research has theoretical and practical significance.