Journal of Positioning, Navigation, and Timing (J Position Navig Timing; JPNT)
Citation: Ju, C., Yoo, J., 2023, Unlabeled Wi-Fi RSSI Indoor Positioning by Using IMU, Journal of Positioning, Navigation, and Timing, 12, 37-42.
Journal of Positioning, Navigation, and Timing (J Position Navig Timing) 2023 March, Volume 12, Issue 1, pages 37-42. https://doi.org/10.11003/JPNT.2023.12.1.37
Received on 30 January 2023, Revised on 24 February 2023, Accepted on 02 March 2023, Published on 30 March 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.
Chanyeong Ju1, Jaehyun Yoo2†
1Department of Future Convergence Technology Engineering, Sungshin Women’s University, Seoul 02844, Korea
2School of AI Convergence, Sungshin Women’s University, Seoul 02844, Korea
†Corresponding Author: E-mail, jhyoo@sungshin.ac.kr; Tel: +82-2-920-7695
Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.
indoor positioning system, unlabeled Wi-Fi RSSI, deep learning
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Conceptualization, J.Y.; methodology, C.J.; software, C.J.; validation, C.J.; formal analysis, J.Y.; investigation, J.Y.; experiment, C.J.; writing—original draft preparation, C.J.; writing—review and editing, J.Y.; funding acquisition, J.Y.
The authors declare no conflict of interest.