Low-Power LoRa Signal-Based Outdoor Positioning Using Fingerprint Algorithm
1
ICT (Computer Software), University of Science and Technology (UST), Daejeon 34113, Korea
2
IOT Research Division, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea
3
Seoul R&D 4G5G Department, Ericsson-LG, Seoul 06232, Korea
4
Embedded S/W Research Department, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(11), 440; https://doi.org/10.3390/ijgi7110440
Received: 31 August 2018 / Revised: 24 October 2018 / Accepted: 4 November 2018 / Published: 9 November 2018
(This article belongs to the Special Issue Geospatial Applications of the Internet of Things (IoT))
Positioning is an essential element in most Internet of Things (IoT) applications. Global Positioning System (GPS) chips have high cost and power consumption, making it unsuitable for long-range (LoRa) and low-power IoT devices. Alternatively, low-power wide-area (LPWA) signals can be used for simultaneous positioning and communication. We summarize previous studies related to LoRa signal-based positioning systems, including those addressing proximity, a path loss model, time difference of arrival (TDoA), and fingerprint positioning methods. We propose a LoRa signal-based positioning method that uses a fingerprint algorithm instead of a received signal strength indicator (RSSI) proximity or TDoA method. The main objective of this study was to evaluate the accuracy and usability of the fingerprint algorithm for large areas in the real world. We estimated the locations using probabilistic means based on three different algorithms that use interpolated fingerprint RSSI maps. The average accuracy of the three proposed algorithms in our experiments was 28.8 m. Our method also reduced the battery consumption significantly compared with that of existing GPS-based positioning methods.
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Keywords:
long-range (LoRa); low-power wide-area (LPWA); fingerprint algorithm; positioning; localization; Internet of Things (IoT)
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MDPI and ACS Style
Choi, W.; Chang, Y.-S.; Jung, Y.; Song, J. Low-Power LoRa Signal-Based Outdoor Positioning Using Fingerprint Algorithm. ISPRS Int. J. Geo-Inf. 2018, 7, 440.
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