research-article

Inertial/magnetic sensors based pedestrian dead reckoning by means of multi-sensor fusion

Authors:

Huosheng HuAuthors Info & Claims

Volume 39, Issue C

Pages 108 - 119

https://doi.org/10.1016/j.inffus.2017.04.006

Published: 01 January 2018 Publication History

Highlights

•

EKF approach is applied to reduce uncertainty and produce better estimations for PDR.

•

A clustering algorithm is proposed to accurately distinguish stance phases.

•

Sensor installation errors and path integral errors are properly corrected.

•

The multi-sensor fusion method has been proved effective by optical apparatus.

Abstract

The challenges of self-contained sensor based pedestrian dead reckoning (PDR) are mainly sensor installation errors and path integral errors caused by sensor variance, and both may dramatically decrease the accuracy of PDR. To address these challenges, this paper presents a multi-sensor fusion based method in which subjects perform specified walking trials at self-administered speeds in both indoor and outdoor scenarios. After an initial calibration with the reduced installation error, quaternion notation is used to represent three-dimensional orientation and an extend Kalman filter (EKF) is deployed to fuse different types of data. A clustering algorithm is proposed to accurately distinguish stance phases, during which integral error can be minimized using Zero Velocity Updates (ZVU) method. The performance of proposed PDR method is evaluated and validated by an optical motion tracking system on healthy subjects. The position estimation accuracy, stride length and foot angle estimation error are studied. Experimental results demonstrate that the proposed self-contained inertial/magnetic sensor based method is capable of providing consistent beacon-free PDR in different scenarios, achieving less than 1% distance error and end-to-end position error.

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Cited By

Pourpanah FEtemad A(2024)Exploring the Landscape of Ubiquitous In-home Health Monitoring: A Comprehensive SurveyACM Transactions on Computing for Healthcare10.1145/36708545:4(1-43)Online publication date: 23-Oct-2024
https://dl.acm.org/doi/10.1145/3670854
Hussien AHeidari AYe XLiang GChen HPan Z(2022)Boosting whale optimization with evolution strategy and Gaussian random walks: an image segmentation methodEngineering with Computers10.1007/s00366-021-01542-039:3(1935-1979)Online publication date: 27-Jan-2022
https://dl.acm.org/doi/10.1007/s00366-021-01542-0
Qiao ZShan WJiang NHeidari AChen HTeng YTurabieh HMafarja M(2022)Gaussian bare‐bones gradient‐based optimizationInternational Journal of Intelligent Systems10.1002/int.2265837:6(3193-3254)Online publication date: 27-Apr-2022
https://dl.acm.org/doi/10.1002/int.22658

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Inertial/magnetic sensors based pedestrian dead reckoning by means of multi-sensor fusion

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Information

Published In

cover image Information Fusion

Information Fusion Volume 39, Issue C

Jan 2018

204 pages

ISSN:1566-2535

Issue’s Table of Contents

Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 January 2018

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Cited By

Pourpanah FEtemad A(2024)Exploring the Landscape of Ubiquitous In-home Health Monitoring: A Comprehensive SurveyACM Transactions on Computing for Healthcare10.1145/36708545:4(1-43)Online publication date: 23-Oct-2024
https://dl.acm.org/doi/10.1145/3670854
Hussien AHeidari AYe XLiang GChen HPan Z(2022)Boosting whale optimization with evolution strategy and Gaussian random walks: an image segmentation methodEngineering with Computers10.1007/s00366-021-01542-039:3(1935-1979)Online publication date: 27-Jan-2022
https://dl.acm.org/doi/10.1007/s00366-021-01542-0
Qiao ZShan WJiang NHeidari AChen HTeng YTurabieh HMafarja M(2022)Gaussian bare‐bones gradient‐based optimizationInternational Journal of Intelligent Systems10.1002/int.2265837:6(3193-3254)Online publication date: 27-Apr-2022
https://dl.acm.org/doi/10.1002/int.22658

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