RTK-LoRa: High-Precision, Long-Range and Energy-Efficient Localization for Mobile IoT devices
2020 (English) In: Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2020Conference paper, Published paper (Refereed)
Abstract [en]
High precision Global Navigation Satellite System (GNSS) is a crucial feature for geo-localization to enhance future applications such as self-driving vehicles. Real-Time Kinematic (RTK) is a promising technology to achieve centimeter precision in GNSS. However, it requires radio communication, which usually is power-hungry and costly, e.g. when using the 4G network. Hence, today RTK is not much exploited in low power energy-efficient devices. In this work, we present a novel sub-meter precision RTK-base system that also achieves the requirements of low power and energy efficiency. The proposed system exploits a novel GNSS module with RTK combined with a long-range and low-power radio (LoRa) to achieve geolocalization with minimal wireless radio infrastructure requirements. We evaluate three different GNSS modules and compare their performance in terms of power and especially precision. Experimental results, with in-field measurements, show an average accuracy of tens of centimeters with a single base station as geostationary reference anchor placed at kilometers of distance from the end-node performing the distance measurement. The peak accuracy measured was below 10cm. © 2020 IEEE.
Place, publisher, year, edition, pages Institute of Electrical and Electronics Engineers Inc. , 2020.
Keywords [en]
Energy Efficiency, Geo-Localization, LoRa, Low Power Sensors, RTK, Geostationary satellites, Global positioning system, Internet of things, Radio broadcasting, Energy efficient, Future applications, Global Navigation Satellite Systems, High-precision, Low power radios, Real time kinematic, Self drivings, Wireless radios, 4G mobile communication systems
Identifiers URN: urn:nbn:se:miun:diva-41580 DOI: 10.1109/SAS48726.2020.9220057 Scopus ID: 2-s2.0-85095569320 ISBN: 9781728148427 (print) OAI: oai:DiVA.org:miun-41580 DiVA, id: diva2:1536151
Conference 2020 IEEE Sensors Applications Symposium, SAS 2020
2021-03-102021-03-102021-04-30 Bibliographically approved