Print Email Facebook Twitter Analysing TDoA Localisation in LoRa Networks Title Analysing TDoA Localisation in LoRa Networks Author Bissett, David (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Software Technology) Contributor Zuniga, Marco (mentor) Kuipers, F.A. (graduation committee) Yorke-Smith, N. (graduation committee) Degree granting institution Delft University of Technology Programme Electrical Engineering | Embedded Systems Date 2018-10-08 Abstract The IoT contains billions of interconnected devices and is only growing larger by the day. These devices often need to operate for years while keeping mobile objects, such as animals or vehicles, connected to a larger system. Therefore they will be battery-powered, energy efficient and, their position will be tracked. Therefore, connecting these devices requires low-power, long-range communication that can also be used for localisation. Because of the scale of the IoT industry, manufacturing and infrastructure costs need to be considered. The low cost, long range and energy efficiency that is required exempts many wireless communication and localisation solutions such as WiFi, GPS and Bluetooth because they are not as suitable as Low-Power Wide-Area Networks (LPWAN's). LoRa is a LPWAN technology that is both Long-Range and cost effective. Therefore, the objective of this thesis is to use a LoRa network for our localisation algorithms.In this work we show that signal strength data becomes turbulent when communicating over a large, urban area. Therefore we evaluate Time Difference of Arrival (TDoA)-based localisation algorithms, including a novel area-based algorithm that we developed. We evaluate the localisation algorithms on a proprietary LoRa network which also provides a localisation service that we use as a benchmark. We evaluate the performance of the algorithms over a large, mostly urban, region of The Netherlands. Using mobile LoRa devices, we show that for 80\% of cases, our proposed algorithm has a position error less than 925m. We also show that the other localisation methods, including the proprietary localisation service, have a larger maximum position error for the same portion of cases. This work contributes a localisation algorithm that can compete against proprietary geolocation services, such as Sigfox and KPN's services, in many applications. Subject LoRalocalisationTDOALoRaWANpositioningIoT To reference this document use: http://resolver.tudelft.nl/uuid:bea423b1-6f04-4708-8ed4-e8663dd51cde Part of collection Student theses Document type master thesis Rights © 2018 David Bissett Files PDF Bissett_DWJ_4620348_MSc_Thesis.pdf 2.82 MB Close viewer /islandora/object/uuid:bea423b1-6f04-4708-8ed4-e8663dd51cde/datastream/OBJ/view