TY - GEN
T1 - Matthan
T2 - 15th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2017
AU - Nguyen, Phuc
AU - Truong, Hoang
AU - Ravindranathan, Mahesh
AU - Nguyen, Anh
AU - Han, Richard
AU - Vu, Tam
N1 - Publisher Copyright:
© 2017 Copyright held by the owner/author(s).
PY - 2017/6/16
Y1 - 2017/6/16
N2 - Drones are increasingly flying in sensitive airspace where their presence may cause harm, such as near airports, forest fires, large crowded events, secure buildings, and even jails. This problem is likely to expand given the rapid proliferation of drones for commerce, monitoring, recreation, and other applications. A cost-e.ective detection system is needed to warn of the presence of drones in such cases. In this paper, we explore the feasibility of inexpensive RF-based detection of the presence of drones. We examine whether physical characteristics of the drone, such as body vibration and body shifting, can be detected in the wireless signal transmitted by drones during communication. We consider whether the received drone signals are uniquely di.erentiated from other mobile wireless phenomena such as cars equipped with Wi-Fi or humans carrying a mobile phone. The sensitivity of detection at distances of hundreds of meters as well as the accuracy of the overall detection system are evaluated using software defined radio (SDR) implementation.
AB - Drones are increasingly flying in sensitive airspace where their presence may cause harm, such as near airports, forest fires, large crowded events, secure buildings, and even jails. This problem is likely to expand given the rapid proliferation of drones for commerce, monitoring, recreation, and other applications. A cost-e.ective detection system is needed to warn of the presence of drones in such cases. In this paper, we explore the feasibility of inexpensive RF-based detection of the presence of drones. We examine whether physical characteristics of the drone, such as body vibration and body shifting, can be detected in the wireless signal transmitted by drones during communication. We consider whether the received drone signals are uniquely di.erentiated from other mobile wireless phenomena such as cars equipped with Wi-Fi or humans carrying a mobile phone. The sensitivity of detection at distances of hundreds of meters as well as the accuracy of the overall detection system are evaluated using software defined radio (SDR) implementation.
UR - http://www.scopus.com/inward/record.url?scp=85026221168&partnerID=8YFLogxK
U2 - 10.1145/3081333.3081354
DO - 10.1145/3081333.3081354
M3 - Conference contribution
AN - SCOPUS:85026221168
T3 - MobiSys 2017 - Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services
SP - 211
EP - 224
BT - MobiSys 2017 - Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services
PB - Association for Computing Machinery, Inc
Y2 - 19 June 2017 through 23 June 2017
ER -