摘要
针对零速校正过程中航向误差观测性差引起的定位精度低的问题,在零速校正的基础上,采用行人步幅和建筑方向辅助的航向误差校正算法,对系统原有观测量扩维。根据行人运动状态得到步幅航向和建筑方向,建立基于速度误差和航向误差的量测模型,利用卡尔曼滤波器实现滤波更新。并且研究了RTS平滑算法,对轨迹进行平滑以解决轨迹突变问题。采用荷兰Xsens公司的MTi-G型IMU进行场地试验,通过对比不同算法的定位误差验证算法的有效性。结果表明,当行人运动距离为70 m时,其最大定位误差不超过3.4 m。
In view of the low positioning accuracy achieved owing to poor observability of the cause of heading error during zero velocity updating（ ZUPT）,on the basis of ZUPT,we propose a heading aided algorithm based on pedestrian stride and the building direction to expand the dimensions of the observation. From the movement of a pedestrian,we obtained the stride direction and building heading. Then,we established a measurement model based on the velocity and heading errors,using a Kalman filter for the update. Furthermore,we investigated the Rauch Rung Streibel（ RTS） smoothing algorithm,and smoothed the trajectory using the RTS smoother to solve the mutation problem. Finally,we conducted experiments to prove the algorithm＇s validity by using the MTi-G inertial measurement unit（ IMU） of Xsens in the Netherlands,and verified the effectiveness of the algorithm by comparing its positioning error with those of different algorithms. The results show that the maximum positioning error does not exceed 3.4 m when the walking distance is 70 m.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2016年第3期408-413,共6页
Journal of Harbin Engineering University
基金
国家自然科学基金资助项目(51379047)
关键词
IMU
零速校正
行人步幅
建筑方向
RTS平滑
定位误差
inertial measurement unit（IMU）
zero velocity updating（ZUPT）
pedestrian stride
building direction
RTS smoothing
positioning error
