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Journal of Central South University

, Volume 26, Issue 8, pp 2281–2294 | Cite as

Hybrid ToA and IMU indoor localization system by various algorithms

  • Xue-chen Chen (陈雪晨)Email author
  • Sheng Chu (楚盛)
  • Fan Li (李繁)
  • Guang Chu (楚广)
Article Thermal and power engineering
  • 20 Downloads

Abstract

In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive Bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line.

Key words

indoor localization time of arrival (ToA) inertial measurement unit (IMU) Bayesian filter extended Kalman filter MAP algorithm 

混合无线传感网和惯性测量装置的室内定位系统

摘要

将惯性导航系统和无线传感网进行结合以提高室内定位的精度。惯性导航系统的关键装置为惯 性测量装置, 其用于测量附着的移动物体的加速度和旋转角。附着在移动目标上的传感器会通过时间 到达法测量与事先放置的锚节点之间的距离。同时将加速度、旋转角和与锚节点之间的距离这些信息 也被传到服务器终端以建立状态转移模型和观察模型, 从而可以应用各种回归贝叶斯算法以实时估计 出移动目标的位置。本文共提出应用三种回归贝叶斯算法。实验表明, 这三种算法不仅不需要移动目 标必须以匀速移动, 而且均在定位精度方面优于单独的ToA 定位方法和单独的步行者航位推算方法。 而其中的两种方法可以用于以任何形式的轨迹曲线移动的目标定位, 也就是不需要受到如下限制, 两 个连续的定位时间点之间通过的轨迹必须是直线。

关键词

室内定位 基于到达时间的测距法定位 贝叶斯滤波器 扩展卡尔曼滤波器 最大后验概率 算法 

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Copyright information

© Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Electronics and Information TechnologySun Yat-Sen UniversityGuangzhouChina
  2. 2.School of Metallurgy and EnvironmentCentral South UniversityChangshaChina

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