TY - GEN
T1 - Investigating cost-effective RF-based detection of drones
AU - Nguyen, Phuc
AU - Ravindranathan, Mahesh
AU - Nguyen, Anh
AU - Han, Richard
AU - Vu, Tam
N1 - Publisher Copyright:
© 2016 Copyright held by the owner/author(s).
PY - 2016/6/26
Y1 - 2016/6/26
N2 - Beyond their benign uses, civilian drones have increasingly been used in problematic ways that have stirred concern from the public and authorities. While many anti-drone systems have been proposed to take them down, such systems often rely on a fundamental assumption that the presence of the drone has already been detected and is known to the defender. However, there is a lack of an automated cost-effective drone detection system. In this paper, we investigate a drone detection system that is designed to autonomously detect and characterize drones using radio frequency wireless signals. In particular, two technical approaches are proposed. The first approach is active tracking where the system sends a radio signal and then listens for its reflected component. The second approach is passive listening where it receives, extracts, and then analyzes observed wireless signal. We perform a set of preliminary experiments to explore the feasibility of the approaches using WARP and USRP software-defined platforms. Our preliminary results illustrate the feasibility of the proposed system and identify the challenges for future research.
AB - Beyond their benign uses, civilian drones have increasingly been used in problematic ways that have stirred concern from the public and authorities. While many anti-drone systems have been proposed to take them down, such systems often rely on a fundamental assumption that the presence of the drone has already been detected and is known to the defender. However, there is a lack of an automated cost-effective drone detection system. In this paper, we investigate a drone detection system that is designed to autonomously detect and characterize drones using radio frequency wireless signals. In particular, two technical approaches are proposed. The first approach is active tracking where the system sends a radio signal and then listens for its reflected component. The second approach is passive listening where it receives, extracts, and then analyzes observed wireless signal. We perform a set of preliminary experiments to explore the feasibility of the approaches using WARP and USRP software-defined platforms. Our preliminary results illustrate the feasibility of the proposed system and identify the challenges for future research.
KW - Drone detection
KW - RF
KW - UAVs
KW - Wireless technology
UR - http://www.scopus.com/inward/record.url?scp=84979878022&partnerID=8YFLogxK
U2 - 10.1145/2935620.2935632
DO - 10.1145/2935620.2935632
M3 - Conference contribution
AN - SCOPUS:84979878022
T3 - DroNet 2016 - Proceedings of the 2nd Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, co-located with MobiSys 2016
SP - 17
EP - 22
BT - DroNet 2016 - Proceedings of the 2nd Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, co-located with MobiSys 2016
PB - Association for Computing Machinery, Inc
T2 - 2nd Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, DroNet 2016
Y2 - 26 June 2016
ER -