RSS Signal Modeling-Based Rapid and Accurate Fingerprinting Database Construction of Indoor Localization Technology

Jung Ho Lee, Taehun Kim, Yongsu Cho, Ju-il Jeon, Kyeong-soo Han, Taikjin Lee

Abstract:	This paper proposes an RF signal modeling technology that can quickly and easily construct a fingerprinting database for Bluetooth beacon signals in indoors. Fingerprinting technology estimates a location by comparing the measured Received Signal Strength (RSS) with the database where RSS is stored for each indoor location. So, the fingerprinting technology is robust to multipath problem, but has the disadvantage that it takes a lot of time and cost to construct the fingerprinting database. The proposed technology consists of the following three processes: (1) beacon arrangement, (2) signal distribution modeling, and (3) model update using measurements. The beacon arrangement process is a process of setting the location of the beacon in coordinate system. The signal distribution modeling process is a process of calculating the RSS value according to the travel distance by computing the signal propagation path from the set beacon location to each indoor location. To reflect signal propagation characteristics (diffraction and penetration) on the propagation model, the proposed technology computes a propagation path of the signal using the A-Star algorithm. It computes signal propagation path using the structure information of indoor map, so it cannot reflect all RF signal changes due to structures and materials in indoors. It utilizes measurements in some areas of the indoor space to correct RSS distribution for the entire indoor space. To verify the performance of the proposed technology, we have performed localization tests by installing 9 Bluetooth beacons on one floor of a building consisting of many pillars and wide halls. When only the modeling result was used as a fingerprinting database, the Root Mean Square Error (RMSE) was 8.1 dBm. After the measurement update, the RMSE was 4.9 dBm. Through this, it was confirmed that the proposed technology can provide high accuracy while significantly reducing time and manpower required for fingerprinting database construction.
Published in:	Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023) September 11 - 15, 2023 Hyatt Regency Denver Denver, Colorado
Pages:	1994 - 1998
Cite this article:	Lee, Jung Ho, Kim, Taehun, Cho, Yongsu, Jeon, Ju-il, Han, Kyeong-soo, Lee, Taikjin, "RSS Signal Modeling-Based Rapid and Accurate Fingerprinting Database Construction of Indoor Localization Technology," Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, September 2023, pp. 1994-1998. https://doi.org/10.33012/2023.19332
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