Pedestrian indoor navigation using foot-mounted IMU with multi-sensor data fusion
Pedestrian indoor navigation using foot-mounted IMU with multi-sensor data fusion
复制标题
使用脚装式 IMU 进行多传感器数据融合的行人室内导航
DOI：
10.1504/ijmic.2018.095833
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Dou Chao
中科院分区：
文献类型：
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作者：
Shengkai Liu;Tingli Su;Binbin Wang;Shiyu Peng;Xue;Yu;Dou Chao
作为一种广泛应用的室内导航技术，基于惯性测量单元（IMU）的方法引起了广泛的研究兴趣。然而，由于传感器的显着和固有的漂移，很难得到准确的行人运动轨迹估计。为了提高行人轨迹的准确性，本文采用了一种脚载惯性测量单元系统，通过融合多个传感器的信息来提高行人轨迹的准确性。结合卡尔曼滤波和零速度更新（ZUPT）方法，得到了一个相当精确的行人轨迹。此外，引入了一些可调参数，以更好地校正位置和速度的估计。通过室内试验验证了该方法的有效性，并通过跑道验证验证了该方法的长航迹性能。
As a widely used indoor navigation technology, the inertial measurement unit (IMU)-based method has caught considerate research interest. However, owing to the significant and inherent drift of the sensors, it is difficult to get the accurate trajectory for pedestrian movement estimation. In this paper, a foot-mounted IMU system was used to improve the accuracy of pedestrian trajectory, by fusing information from the multiple sensors. With the Kalman filter combined with the zero-velocity update (ZUPT) method, a reasonably accurate pedestrian trajectory was then obtained. Furthermore, some adjustable parameters were introduced to better correct the estimation of position and velocity. Effectiveness of the proposed method was well verified through the indoor experiments and the long track performance was also tested in runway verification.