CSE Master's Thesis: Ali Ghubaish

Dec 14, 2017
2 p.m.
4 p.m.
Jolley Hall, Room 431

“Locating Unmanned Aerial Vehicles (UAVs)”.

Ali Ghubaish
Adviser: Raj Jain

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 authorities to be alerted when any UAV is breaching restricted areas. Thus, a proper UAV location system can prevent UAVs breaching any restricted area. 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 parameters: time, 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 parameters and also has minimal cost. Therefore, RSSI was used to estimate the distance between the UAV and one of the ground stations. Location of the UAV including its height can be determined using four ground stations and using their estimated distance from the UAV. Several factors that may affect the measured RSSI are also discussed. These include different environments, antenna directions, and different messages lengths.