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Novel Drift Reduction Methods in Foot-Mounted PDR System

The zero-velocity update (ZUPT)-aided extended Kalman filter (EKF) is commonly used in the traditional inertial navigation system (INS)-based foot-mounted pedestrian dead reckoning (PDR) system, which can effectively suppress the error growth of the inertial-based pedestrian navigation systems. Howe...

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Detalles Bibliográficos
Autores principales: Zhang, Wenchao, Wei, Dongyan, Yuan, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766805/
https://www.ncbi.nlm.nih.gov/pubmed/31540322
http://dx.doi.org/10.3390/s19183962
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author Zhang, Wenchao
Wei, Dongyan
Yuan, Hong
author_facet Zhang, Wenchao
Wei, Dongyan
Yuan, Hong
author_sort Zhang, Wenchao
collection PubMed
description The zero-velocity update (ZUPT)-aided extended Kalman filter (EKF) is commonly used in the traditional inertial navigation system (INS)-based foot-mounted pedestrian dead reckoning (PDR) system, which can effectively suppress the error growth of the inertial-based pedestrian navigation systems. However, in the realistic test, the system still often suffers from drift, which is commonly caused by two reasons: failed detection of the stationary phase in the dynamic pedestrian gait and heading drift, which is a poorly observable variable of the ZUPT method. In this paper, firstly, in order to improve the initial heading alignment accuracy, a novel method to calibrate the PDR system’s initial absolute heading is proposed which is based on the geometric method. By using a calibration line rather than only using the heading of the starting point, the method can calibrate the initial heading of the PDR system more accurately. Secondly, for the problem of failed detection of the stationary phase in the dynamic pedestrian gait, a novel stationary phase detection method is proposed, which is based on foot motion periodicity rather than the threshold comparison principle in the traditional method. In an experiment, we found that the zero-speed state points always occur around the minimum value of the stationary detector in each gait cycle. By taking the minimum value in each gait cycle as the zero-speed state point, it can effectively reduce the failed detection of the zero-speed interval. At last, in order to reduce the heading drifts during walking over time, a new motion constraint method is exploited based on the range constraint principle. During pedestrian walking, the distance between the foot position estimates of the current moment and the previous stationary period is within the maximum stride length. Once the distance is greater than the maximum stride length, the constraint method is used to confine the current estimated foot position to the sphere of the maximum stride length relative to the previous stationary foot position. Finally, the effectiveness of all proposed methods is verified by the experiments.
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spelling pubmed-67668052019-10-02 Novel Drift Reduction Methods in Foot-Mounted PDR System Zhang, Wenchao Wei, Dongyan Yuan, Hong Sensors (Basel) Article The zero-velocity update (ZUPT)-aided extended Kalman filter (EKF) is commonly used in the traditional inertial navigation system (INS)-based foot-mounted pedestrian dead reckoning (PDR) system, which can effectively suppress the error growth of the inertial-based pedestrian navigation systems. However, in the realistic test, the system still often suffers from drift, which is commonly caused by two reasons: failed detection of the stationary phase in the dynamic pedestrian gait and heading drift, which is a poorly observable variable of the ZUPT method. In this paper, firstly, in order to improve the initial heading alignment accuracy, a novel method to calibrate the PDR system’s initial absolute heading is proposed which is based on the geometric method. By using a calibration line rather than only using the heading of the starting point, the method can calibrate the initial heading of the PDR system more accurately. Secondly, for the problem of failed detection of the stationary phase in the dynamic pedestrian gait, a novel stationary phase detection method is proposed, which is based on foot motion periodicity rather than the threshold comparison principle in the traditional method. In an experiment, we found that the zero-speed state points always occur around the minimum value of the stationary detector in each gait cycle. By taking the minimum value in each gait cycle as the zero-speed state point, it can effectively reduce the failed detection of the zero-speed interval. At last, in order to reduce the heading drifts during walking over time, a new motion constraint method is exploited based on the range constraint principle. During pedestrian walking, the distance between the foot position estimates of the current moment and the previous stationary period is within the maximum stride length. Once the distance is greater than the maximum stride length, the constraint method is used to confine the current estimated foot position to the sphere of the maximum stride length relative to the previous stationary foot position. Finally, the effectiveness of all proposed methods is verified by the experiments. MDPI 2019-09-13 /pmc/articles/PMC6766805/ /pubmed/31540322 http://dx.doi.org/10.3390/s19183962 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Wenchao
Wei, Dongyan
Yuan, Hong
Novel Drift Reduction Methods in Foot-Mounted PDR System
title Novel Drift Reduction Methods in Foot-Mounted PDR System
title_full Novel Drift Reduction Methods in Foot-Mounted PDR System
title_fullStr Novel Drift Reduction Methods in Foot-Mounted PDR System
title_full_unstemmed Novel Drift Reduction Methods in Foot-Mounted PDR System
title_short Novel Drift Reduction Methods in Foot-Mounted PDR System
title_sort novel drift reduction methods in foot-mounted pdr system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766805/
https://www.ncbi.nlm.nih.gov/pubmed/31540322
http://dx.doi.org/10.3390/s19183962
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