Abstract
Despite the popularity and usefulness of Unmanned Aerial Vehicles (UAVs) or drones, they are not allowed to fly in some areas without prior permission from the Federal Aviation Administration (FAA). However, many incidents of UAVs breaching such restrictions have been reported. A UAV location system can help the law enforcement to be alerted and can prevent UAVs breaching any restricted area without permission. This master thesis proposes a UAV location system where each UAV has a unique identification tag. The method consists of two stages: distance and location estimation. We compared distance estimation using three different methods: Time of Arrival (ToA), counter, and Received Signal Strength Indication (RSSI). Long Range Wide Area Network (LoRaWAN) protocol is utilized in the system. Initial results have shown that RSSI is the most accurate among the three methods and also has a minimal cost. Therefore, RSSI was used to estimate the distance between the UAV and each of the ground stations. Location of the UAV can be determined using four ground stations coordinates and their estimated distance from the UAV. Several factors that may affect the measured RSSI are also discussed. These include different environments, different heights, antenna directions, and different message lengths.
Committee Chair
Raj Jain
Committee Members
Raj Jain, Chair Roger Chamberlain Ben Moseley
Degree
Master of Engineering (ME)
Author's Department
Computer Science & Engineering
Document Type
Thesis
Date of Award
Fall 12-20-2017
Language
English (en)
DOI
https://doi.org/10.7936/K73B5XMR
Recommended Citation
Ghubaish, Ali, "Locating Unmanned Aerial Vehicles (UAVs)" (2017). McKelvey School of Engineering Theses & Dissertations. 269.
The definitive version is available at https://doi.org/10.7936/K73B5XMR
Comments
Permanent URL: https://doi.org/10.7936/K73B5XMR