Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying Position

Pedestrian dead reckoning (PDR) is an essential technology for positioning and navigation in complex indoor environments. In the process of PDR positioning and navigation using mobile phones, gait information acquired by inertial sensors under various carrying positions differs from noise contained...

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Main Authors: Ying Guo, Qinghua Liu, Xianlei Ji, Shengli Wang, Mingyang Feng, Yuxi Sun
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Mobile Information Systems
Online Access:http://dx.doi.org/10.1155/2019/4709501
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spelling doaj-7bb677670e224ca0a6d7c8f3b618e3932021-07-02T05:06:53ZengHindawi LimitedMobile Information Systems1574-017X1875-905X2019-01-01201910.1155/2019/47095014709501Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying PositionYing Guo0Qinghua Liu1Xianlei Ji2Shengli Wang3Mingyang Feng4Yuxi Sun5College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaInstitute of Ocean Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaChinese Academy of Surveying and Mapping, Beijing 100830, ChinaPedestrian dead reckoning (PDR) is an essential technology for positioning and navigation in complex indoor environments. In the process of PDR positioning and navigation using mobile phones, gait information acquired by inertial sensors under various carrying positions differs from noise contained in the heading information, resulting in excessive gait detection deviation and greatly reducing the positioning accuracy of PDR. Using data from mobile phone accelerometer and gyroscope signals, this paper examined various phone carrying positions and switching positions as the research objective and analysed the time domain characteristics of the three-axis accelerometer and gyroscope signals. A principal component analysis algorithm was used to reduce the dimension of the extracted multidimensional gait feature, and the extracted features were random forest modelled to distinguish the phone carrying positions. The results show that the step detection and distance estimation accuracy in the gait detection process greatly improved after recognition of the phone carrying position, which enhanced the robustness of the PDR algorithm.http://dx.doi.org/10.1155/2019/4709501
collection DOAJ
language English
format Article
sources DOAJ
author Ying Guo
Qinghua Liu
Xianlei Ji
Shengli Wang
Mingyang Feng
Yuxi Sun
spellingShingle Ying Guo
Qinghua Liu
Xianlei Ji
Shengli Wang
Mingyang Feng
Yuxi Sun
Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying Position
Mobile Information Systems
author_facet Ying Guo
Qinghua Liu
Xianlei Ji
Shengli Wang
Mingyang Feng
Yuxi Sun
author_sort Ying Guo
title Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying Position
title_short Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying Position
title_full Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying Position
title_fullStr Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying Position
title_full_unstemmed Multimode Pedestrian Dead Reckoning Gait Detection Algorithm Based on Identification of Pedestrian Phone Carrying Position
title_sort multimode pedestrian dead reckoning gait detection algorithm based on identification of pedestrian phone carrying position
publisher Hindawi Limited
series Mobile Information Systems
issn 1574-017X
1875-905X
publishDate 2019-01-01
description Pedestrian dead reckoning (PDR) is an essential technology for positioning and navigation in complex indoor environments. In the process of PDR positioning and navigation using mobile phones, gait information acquired by inertial sensors under various carrying positions differs from noise contained in the heading information, resulting in excessive gait detection deviation and greatly reducing the positioning accuracy of PDR. Using data from mobile phone accelerometer and gyroscope signals, this paper examined various phone carrying positions and switching positions as the research objective and analysed the time domain characteristics of the three-axis accelerometer and gyroscope signals. A principal component analysis algorithm was used to reduce the dimension of the extracted multidimensional gait feature, and the extracted features were random forest modelled to distinguish the phone carrying positions. The results show that the step detection and distance estimation accuracy in the gait detection process greatly improved after recognition of the phone carrying position, which enhanced the robustness of the PDR algorithm.
url http://dx.doi.org/10.1155/2019/4709501
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