TY - GEN
T1 - Towards RF-based localization of a drone and its controller
AU - Nguyen, Phuc
AU - Kim, Taeho
AU - Miao, Jinpeng
AU - Hesselius, Daniel
AU - Kenneally, Erin
AU - Massey, Daniel
AU - Frew, Eric
AU - Han, Richard
AU - Vu, Tam
PY - 2019
Y1 - 2019
N2 - Drones are increasingly disrupting sensitive airspace around airports, as evidenced by the recent shutdown of Gatwick Airport for over a day by a drone incursion, as well as other incidents at Dubai airport, one of the busiest airports in the world. As a result, there is heightened interest in being able to detect and track drones. This paper explores a system that can use a cost-e.ective passive RF-based approach to determine from which direction a drone is approaching as well as its location, and also determine from which direction its controller is transmitting and the controller's location. The system combines angle of arrival (AoA) techniques with RFbased signal analysis to determine whether a peak in incoming RF signal strength at a given direction corresponds to a drone or its controller, and utilizes triangulation to estimate their locations. Our experiments demonstrate that a system consisting of inexpensive software de.ned radios (SDRs) and rotating antennas can e.ectively estimate the angle of arrival and location of both a drone and its controller.
AB - Drones are increasingly disrupting sensitive airspace around airports, as evidenced by the recent shutdown of Gatwick Airport for over a day by a drone incursion, as well as other incidents at Dubai airport, one of the busiest airports in the world. As a result, there is heightened interest in being able to detect and track drones. This paper explores a system that can use a cost-e.ective passive RF-based approach to determine from which direction a drone is approaching as well as its location, and also determine from which direction its controller is transmitting and the controller's location. The system combines angle of arrival (AoA) techniques with RFbased signal analysis to determine whether a peak in incoming RF signal strength at a given direction corresponds to a drone or its controller, and utilizes triangulation to estimate their locations. Our experiments demonstrate that a system consisting of inexpensive software de.ned radios (SDRs) and rotating antennas can e.ectively estimate the angle of arrival and location of both a drone and its controller.
KW - Drones/UAVs/UASs localization
KW - Passive RF
KW - Wireless technology
UR - http://www.scopus.com/inward/record.url?scp=85069219635&partnerID=8YFLogxK
U2 - 10.1145/3325421.3329766
DO - 10.1145/3325421.3329766
M3 - Conference proceeding contribution
T3 - DroNet 2019 - Proceedings of the 5th Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, co-located with MobiSys 2019
SP - 21
EP - 26
BT - DroNet 2019 - Proceedings of the 5th Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, co-located with MobiSys 2019
PB - Association for Computing Machinery, Inc
CY - New York, NY
T2 - 5th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, DroNet 2019, co-located with MobiSys 2019
Y2 - 21 June 2019 through 21 June 2019
ER -