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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Hindawi Limited
2019-01-01
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Series: | Mobile Information Systems |
Online Access: | http://dx.doi.org/10.1155/2019/4709501 |
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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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