Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices

Chen Zhaoyi; Du Xiaojing; Li Huaijian

doi:doi:10.11648/j.sd.20170506.12

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Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices

Chen Zhaoyi, Du Xiaojing, Li Huaijian

Published in Science Discovery (Volume 5, Issue 6)

Received: 25 October 2017 Published: 27 October 2017

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Abstract

Pedestrian navigation system (PNS) is also known as the walker navigation system, which is mainly used to track and posit real-time position of walker, to provide walk speed and position of walker, and also be applied to military, science, sport, rescue, the blind navigation, electronic product, etc. GPS signal is unreliable and difficult to provide accurate location information in most environments such as indoor, urban streets and canyons. At this point, the autonomous navigation system based on the proposed algorithm is a good solution. This article mainly analyzes the MEMS inertial device in the actual engineering practice, the application of the low precision of MEMS inertial device used in personal navigation correction algorithm, and combines the MEMS inertial sensors and GPS receiver, satisfies the requirement of pedestrian positioning. Using the complementary filter to fuse sensor data, we can obtain information of high precision orientation.

Published in	Science Discovery (Volume 5, Issue 6)
DOI	10.11648/j.sd.20170506.12
Page(s)	410-415
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

MEMS Inertial Devices, Air Position Calculation, Kalman Filtering

References

[1]	陈尚，张世军，穆星科．MEMS陀螺技术国内外发展现状简述[J]．技术与应用2016 (2):19-23。
[2]	王勇，张斌，冯运辉．微工程与惯性测量组件微型化发展研究[J]．导航与控制2011 (5):64-68。
[3]	Kwakkel S, Lachapelle G, Cannon M E. GNSS aided in situhuman kinematics during running [C]. Proceedings of GNSS08. The Institute of Navigation, 2008.
[4]	Renaudin V, Yalak O, Tome P, et al. Indoor navigation of emergency agents [J]. European Journal of Navigation, 2007, 5 (3).
[5]	崔潇，秦永元，周琪．鞋式个人导航系统算法和试验研究[J]．测控技术2013 (32):138-142。
[6]	张金亮，秦永元，梅春波．基于MEMS惯性技术的鞋式行人导航系统[J]．中国惯性技术学报2011 (6):253-256。
[7]	Foxlin E. Pedestrian tracking with shoe-mounted inertial sensor [J]. IEEE Computer Graphics and Applications, 2005, 25 (6): 38-46.
[8]	许睿，孙永荣，陈武，刘建业．一种基于抗差滤波的行人导航算法研究[J]．系统工程与电子技术2010(7):1506-1508。
[9]	Retscher G. Test and integration of location sensors for a multisensory personal navigation [J]. The Journal of Navigation, 2007, 60 (1): 107-117.
[10]	C. Huang, Z. Liao, and L. Zhao. Synergism of INS and PDR in self-contained pedestrian tracking with a miniature sensor module [J]. IEEE Sensor J, 2010, 8 :1349-1359.
[11]	Renaudin, V, Yalak, O, and Tome, P. Hybridization of MEMS and Assisted GPS for Pedestrian Navigation [J]. Inside GNSS, 2007, 1, 34-42.

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APA Style

Chen Zhaoyi, Du Xiaojing, Li Huaijian. (2017). Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices. Science Discovery, 5(6), 410-415. https://doi.org/10.11648/j.sd.20170506.12

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ACS Style

Chen Zhaoyi; Du Xiaojing; Li Huaijian. Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices. Sci. Discov. 2017, 5(6), 410-415. doi: 10.11648/j.sd.20170506.12

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AMA Style

Chen Zhaoyi, Du Xiaojing, Li Huaijian. Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices. Sci Discov. 2017;5(6):410-415. doi: 10.11648/j.sd.20170506.12

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@article{10.11648/j.sd.20170506.12,
  author = {Chen Zhaoyi and Du Xiaojing and Li Huaijian},
  title = {Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices},
  journal = {Science Discovery},
  volume = {5},
  number = {6},
  pages = {410-415},
  doi = {10.11648/j.sd.20170506.12},
  url = {https://doi.org/10.11648/j.sd.20170506.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170506.12},
  abstract = {Pedestrian navigation system (PNS) is also known as the walker navigation system, which is mainly used to track and posit real-time position of walker, to provide walk speed and position of walker, and also be applied to military, science, sport, rescue, the blind navigation, electronic product, etc. GPS signal is unreliable and difficult to provide accurate location information in most environments such as indoor, urban streets and canyons. At this point, the autonomous navigation system based on the proposed algorithm is a good solution. This article mainly analyzes the MEMS inertial device in the actual engineering practice, the application of the low precision of MEMS inertial device used in personal navigation correction algorithm, and combines the MEMS inertial sensors and GPS receiver, satisfies the requirement of pedestrian positioning. Using the complementary filter to fuse sensor data, we can obtain information of high precision orientation.},
 year = {2017}
}

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TY  - JOUR
T1  - Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices
AU  - Chen Zhaoyi
AU  - Du Xiaojing
AU  - Li Huaijian
Y1  - 2017/10/27
PY  - 2017
N1  - https://doi.org/10.11648/j.sd.20170506.12
DO  - 10.11648/j.sd.20170506.12
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 410
EP  - 415
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20170506.12
AB  - Pedestrian navigation system (PNS) is also known as the walker navigation system, which is mainly used to track and posit real-time position of walker, to provide walk speed and position of walker, and also be applied to military, science, sport, rescue, the blind navigation, electronic product, etc. GPS signal is unreliable and difficult to provide accurate location information in most environments such as indoor, urban streets and canyons. At this point, the autonomous navigation system based on the proposed algorithm is a good solution. This article mainly analyzes the MEMS inertial device in the actual engineering practice, the application of the low precision of MEMS inertial device used in personal navigation correction algorithm, and combines the MEMS inertial sensors and GPS receiver, satisfies the requirement of pedestrian positioning. Using the complementary filter to fuse sensor data, we can obtain information of high precision orientation.
VL  - 5
IS  - 6
ER  -

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Author Information

Chen Zhaoyi

Aerospace Institute, Beijing Institute of Technology, Beijing, China
Du Xiaojing

Aerospace Institute, Beijing Institute of Technology, Beijing, China
Li Huaijian

Aerospace Institute, Beijing Institute of Technology, Beijing, China

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APA Style

Chen Zhaoyi, Du Xiaojing, Li Huaijian. (2017). Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices. Science Discovery, 5(6), 410-415. https://doi.org/10.11648/j.sd.20170506.12

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ACS Style

Chen Zhaoyi; Du Xiaojing; Li Huaijian. Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices. Sci. Discov. 2017, 5(6), 410-415. doi: 10.11648/j.sd.20170506.12

Copy | Download

AMA Style

Chen Zhaoyi, Du Xiaojing, Li Huaijian. Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices. Sci Discov. 2017;5(6):410-415. doi: 10.11648/j.sd.20170506.12

Copy | Download

@article{10.11648/j.sd.20170506.12,
  author = {Chen Zhaoyi and Du Xiaojing and Li Huaijian},
  title = {Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices},
  journal = {Science Discovery},
  volume = {5},
  number = {6},
  pages = {410-415},
  doi = {10.11648/j.sd.20170506.12},
  url = {https://doi.org/10.11648/j.sd.20170506.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20170506.12},
  abstract = {Pedestrian navigation system (PNS) is also known as the walker navigation system, which is mainly used to track and posit real-time position of walker, to provide walk speed and position of walker, and also be applied to military, science, sport, rescue, the blind navigation, electronic product, etc. GPS signal is unreliable and difficult to provide accurate location information in most environments such as indoor, urban streets and canyons. At this point, the autonomous navigation system based on the proposed algorithm is a good solution. This article mainly analyzes the MEMS inertial device in the actual engineering practice, the application of the low precision of MEMS inertial device used in personal navigation correction algorithm, and combines the MEMS inertial sensors and GPS receiver, satisfies the requirement of pedestrian positioning. Using the complementary filter to fuse sensor data, we can obtain information of high precision orientation.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Research on Pedestrian Navigation Algorithm Based on MEMS Inertial Devices
AU  - Chen Zhaoyi
AU  - Du Xiaojing
AU  - Li Huaijian
Y1  - 2017/10/27
PY  - 2017
N1  - https://doi.org/10.11648/j.sd.20170506.12
DO  - 10.11648/j.sd.20170506.12
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 410
EP  - 415
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20170506.12
AB  - Pedestrian navigation system (PNS) is also known as the walker navigation system, which is mainly used to track and posit real-time position of walker, to provide walk speed and position of walker, and also be applied to military, science, sport, rescue, the blind navigation, electronic product, etc. GPS signal is unreliable and difficult to provide accurate location information in most environments such as indoor, urban streets and canyons. At this point, the autonomous navigation system based on the proposed algorithm is a good solution. This article mainly analyzes the MEMS inertial device in the actual engineering practice, the application of the low precision of MEMS inertial device used in personal navigation correction algorithm, and combines the MEMS inertial sensors and GPS receiver, satisfies the requirement of pedestrian positioning. Using the complementary filter to fuse sensor data, we can obtain information of high precision orientation.
VL  - 5
IS  - 6
ER  -

Copy | Download