Pedestrian Indoor Navigation System Using Inertial Measurement Unit

M. B. Dehkordi, A. Frisoli, E. Sotgiu, C. Loconsole
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引用次数: 11

Abstract

This paper presents a method for an indoor pedestrian localization, based on the data that solely are measured by a foot-mounted Inertial Measurement Unit (IMU). To locate the user accurately, a comprehensive Extended Kalman Filter (EKF) with five states is developed. Five different error reduction methods are employed to estimate the errors of all five states. These error reduction methods feed EKF independently, at stance phases or different time intervals of swing phases. The navigation system is developed using the accelerometer and gyroscope measurements and without magnetometer, thus it is insensitive to the presence of metal and magnetic fields, and it is able to estimate the user’s tracked trajectory with the same accuracy in both indoor and outdoor environments. The system does not rely on the measurement from external infrastructure (e.g., RFID). To evaluate the accuracy of the system, several experimental tests are carried out over the known trajectories. Results demonstrate that the error of the estimated tracked trajectory is less than 1% of the total traveled distance.
基于惯性测量单元的行人室内导航系统
本文提出了一种基于足部惯性测量单元(IMU)测量数据的室内行人定位方法。为了准确定位用户,提出了一种具有五种状态的综合扩展卡尔曼滤波器。采用五种不同的误差减小方法来估计这五种状态的误差。这些减小误差的方法分别在摆相或摆相的不同时间间隔独立地馈入EKF。该导航系统采用加速度计和陀螺仪测量,不使用磁力计,因此对金属和磁场的存在不敏感,能够在室内和室外环境下以相同的精度估计用户的跟踪轨迹。该系统不依赖于来自外部基础设施(例如RFID)的测量。为了评估系统的准确性,在已知的轨迹上进行了几次实验测试。结果表明,估计的跟踪轨迹误差小于总行程的1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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