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.
","abstract_html":"<p>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.</p>","abstract_has_math":false,"creators":["Ghubaish, Ali"],"institution":null,"degree_name":"Master of Engineering (ME)","degree_level":"Thesis","degree_discipline":"Computer Science & Engineering","degree_department":null,"school":null,"contributors":["Raj Jain","Raj Jain, Chair Roger Chamberlain Ben Moseley"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-12-20T08:00:00Z","date_published":"2017-12-20T08:00:00Z","updated_at":"2026-07-24T06:13:55Z","subjects":["UAV","Location","LoRaWAN","Engineering"],"languages":["English (en)"],"rights":["I have not registered my thesis with the U.S. Copyright Office, and do not intend to."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openscholarship.wustl.edu/eng_etds/269"],"render_values":[{"text":"https://openscholarship.wustl.edu/eng_etds/269","href":"https://openscholarship.wustl.edu/eng_etds/269","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.7936/K73B5XMR","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Raj Jain","Raj Jain, Chair Roger Chamberlain Ben Moseley"]},{"key":"dc:creator","label":"Author","values":["Ghubaish, Ali"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2022-06-21T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science & Engineering","McKelvey School of Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Engineering (ME)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["UAV","Location","LoRaWAN","Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English (en)"]},{"key":"dc:rights","label":"Dc Rights","values":["I have not registered my thesis with the U.S. Copyright Office, and do not intend to."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://doi.org/10.7936/K73B5XMR","https://openscholarship.wustl.edu/eng_etds/269"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Permanent URL: https://doi.org/10.7936/K73B5XMR"]},{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Locating Unmanned Aerial Vehicles (UAVs)"]}]}],"canonical_facts":{"dc:contributor":["Raj Jain","Raj Jain, Chair Roger Chamberlain Ben Moseley"],"dc:creator":["Ghubaish, Ali"],"dc:date.available":["2022-06-21T07:00:00Z"],"dc:description":["Permanent URL: https://doi.org/10.7936/K73B5XMR"],"dc:description.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.
"],"dc:identifier":["https://doi.org/10.7936/K73B5XMR","https://openscholarship.wustl.edu/eng_etds/269"],"dc:language":["English (en)"],"dc:rights":["I have not registered my thesis with the U.S. Copyright Office, and do not intend to."],"dc:subject":["UAV","Location","LoRaWAN","Engineering"],"dc:title":["Locating Unmanned Aerial Vehicles (UAVs)"],"thesis:degree_discipline":["Computer Science & Engineering","McKelvey School of Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Engineering (ME)"]},"updated_at":"2026-07-24T06:13:55Z"}