Journal of Positioning, Navigation, and Timing (J Position Navig Timing; JPNT)
Indexed in KCI (Korea Citation Index)
OPEN ACCESS, PEER REVIEWED
pISSN 2288-8187
eISSN 2289-0866

Walking/Non-walking and Indoor/Outdoor Cognitive-based PDR/GPS/ WiFi Integrated Pedestrian Navigation for Smartphones

CONTENTS

Research article

Citation: Cho, E. Y., Kwon, J. U., Cho, S. Y., Yoo, J.J., & Seo, S. 2023, Walking/Non-walking and Indoor/Outdoor Cognitive-based PDR/GPS/ WiFi Integrated Pedestrian Navigation for Smartphones, Journal of Positioning, Navigation, and Timing, 12, 399-408.

Journal of Positioning, Navigation, and Timing (J Position Navig Timing) 2023 December, Volume 12, Issue 4, pages 399-408. https://doi.org/10.11003/JPNT.2023.12.4.399

Received on 14 November 2023, Revised on 29 November 2023, Accepted on 01 December 2023, Published on 15 December 2023.

License: Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/bync/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Walking/Non-walking and Indoor/Outdoor Cognitive-based PDR/GPS/ WiFi Integrated Pedestrian Navigation for Smartphones

Eui Yeon Cho1, Jae Uk Kwon1, Seong Yun Cho2,3†, JaeJun Yoo4†, Seonghun Seo4

1Department of IT Engineering, Kyungil University, Gyeongsan 38428, Korea

2School of Smart Design Engineering, Kyungil University, Gyeongsan 38428, Korea

3NavIn Labs Co., Ltd, Daegu 41066, Korea 4Mobility UX Section, Electronics and Telecommunications Research Institute, Daejeon 34129, Korea

Corresponding Author: E-mail, sycho@kiu.kr / jjryu@etri.re.kr; Tel, +82-53-600-5584 / +82-42-860-1011

Abstract

In this paper, we propose a Correction Dead Reckoning (CDR) solution using correction information such as Map Matching FeedBack (MMFB) in an underground parking lot. In order to correct position errors in an underground parking lot, vehicle position and heading errors are corrected using MMFB information in road link properties. The proposed method was applied to an in-vehicle navigation system and tested. The experimental results show that the proposed robust dead reckoning solution corrects Dead Reckoning (DR) position errors that occur when driving for a long time in an underground parking lot.

Keywords

smartphone PDR, GPS DOP, WiFi fingerprinting, integrated pedestrian navigation, cognition

References

Cho, E. Y., Kwon, J. U., Chae, M. S., Cho, S. Y., Yoo, J., et al. 2023, Indoor Positioning Technology Integrating Pedestrian Dead Reckoning and WiFi Fingerprinting Based on EKF with Adaptive Error Covariance, Journal of Positioning, Navigation, and Timing, 12, 271-280. https://doi.org/10.11003/JPNT.2023.12.3.271

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Cho, S. Y., Lee, J. H., & Park, C. G. 2022, A Zero-Velocity Detection Algorithm Robust to Various Gait Types for Pedestrian Inertial Navigation, IEEE Sensors Journal, 22, 4916-4931. https://doi.org/10.1109/JSEN.2021.306408

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Kwon, J. U., Chae, M. S., Cho, E., Y., & Cho, S. Y. 2023, Fast Generation of Wi-Fi Positioning Fingerprint Database Using Reference Location Information Acquired Based on 1D-PDR, IPIN 2023, Nuremberg, Germany, 25-28 September 2023.

Kwon, J. U., Chae, M. S., & Cho, S. Y. 2022, CNN-based Adaptive K for Improving Positioning Accuracy in W-kNN-based LTE Fingerprint Positioning, Journal of Positioning, Navigation, and Timing, 11, 217-227. https://doi.org/10.11003/JPNT.2022.11.3.217

Sara, K., Mahbub, H., & Aruna, S. 2014, Feature Selection for Floor-changing Activity Recognition in Multi-Floor Pedestrian Navigation, ICMU. https://doi.org/10.1109/ ICMU.2014.6799049

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Xia, S., Liu, Y., Yuan, G., Zhu, M., & Wang, Z. 2017, Indoor Fingerprint Positioning Based on Wi-Fi: An Overview, ISPRS International Journal of Geo-Information, 6, 135. https://doi.org/10.3390/ijgi6050135

Acknowledgments

This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant RS2022-00141819).

Author contributIons

Eui Yeon Cho contributed to the design and implementation of the PDR and integration algorithms and to the writing of the manuscript. Jae Uk Kwon contributed to the design and implementation of the WiFi fingerprinting algorithm. Seong Yun Cho led the research and reviewed the manuscript as the person in charge of the service project. JaeJun Yoo and Seonghun Seo supervised the research as original project managers and provided related information.

Conflicts of interest

The authors declare no conflict of interest.