Indoor pedestrian dead reckoning method based on multi-sensor data fusion

LIU Sheng-kai; SU Ting-li; WANG Bin-bin; JIN Xue-bo; PENG Shi-yu

doi:10.13873/j.1000-9787(2018)03-0133-05

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Indoor pedestrian dead reckoning method based on multi-sensor data fusion

更新时间：2025-09-11

- Indoor pedestrian dead reckoning method based on multi-sensor data fusion
- Vol. 37, Issue 3, Pages: 133-137(2018)
- 作者机构：
  
  北京工商大学计算机与信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-9787(2018)03-0133-05
  CLC： TP212.9
- Published：2018
- 稿件说明：
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[1]柳胜凯,苏婷立,王彬彬,金学波,彭世禹.基于多传感器数据融合的室内行人航位推算法[J].传感器与微系统,2018,37(03):133-137.

LIU Sheng-kai, SU Ting-li, WANG Bin-bin, et al. Indoor pedestrian dead reckoning method based on multi-sensor data fusion[J]. 2018, 37(3): 133-137.
[1]柳胜凯,苏婷立,王彬彬,金学波,彭世禹.基于多传感器数据融合的室内行人航位推算法[J].传感器与微系统,2018,37(03):133-137. DOI： 10.13873/j.1000-9787(2018)03-0133-05.

LIU Sheng-kai, SU Ting-li, WANG Bin-bin, et al. Indoor pedestrian dead reckoning method based on multi-sensor data fusion[J]. 2018, 37(3): 133-137. DOI： 10.13873/j.1000-9787(2018)03-0133-05.

摘要

针对惯性测量单元（IMU）本身存在测量漂移

很难获得精确的室内行人轨迹的问题

提出了使用多个传感器信息融合的方案

包括IMU和视频摄像头

并结合卡尔曼滤波和零速检测算法进行参数优化

以提高行人运动轨迹的精度。仿真结果表明:算法可以有效降低行人轨迹的误差。

Abstract

Due to drift of measuremen of inertial measurement unit（ IMU）

it is difficult to get accurate trajectory of pedestrian indoor

a scheme fusing multiple sensors information is proposed

include inertial measurement unit（ IMU） and vedio camera

combined Kalman filtering with zero-velocity detection algorithm for parameters optimization. The simulation results show that the algorithm can effectively reduce the error of pedestrian trajectory.

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references

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不同惯导系统零速检测算法的性能分析 [J]. 石波,李耀宗,程敏,杨伟彬. 山东科技大学学报(自然科学版) . 2016(02)

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