Predictive Tracking of a High Capability Malicious UAV
Paper
Paper/Presentation Title | Predictive Tracking of a High Capability Malicious UAV |
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Presentation Type | Paper |
Authors | Brown, Jason (Author) and Raj, Nawin (Author) |
Journal or Proceedings Title | Proceedings of 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC) |
Number of Pages | 6 |
Year | 2021 |
Place of Publication | Piscataway, United States |
ISBN | 9781665414906 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/CCWC51732.2021.9376137 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/9376137 |
Conference/Event | IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC 2021) |
Event Details | IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC 2021) Event Date 27 to end of 30 Jan 2021 Event Location Las Vegas, United States |
Abstract | There is considerable interest in researching methods of deterring, detecting and mitigating the actions of malicious UAVs which can cause service interruption and/or physical damage to civilian infrastructure. One of many methods that have been proposed is to passively track a malicious UAV to its final destination using a swarm of surveillance UAVs. A high capability malicious UAV can outrun any one pursuing UAV, so tracking responsibility must be continually handed over from one pursuing UAV to another in the swarm over time. In this paper, we build on previous research to show how, once a high capability malicious UAV is detected by one member of the swarm of surveillance UAVs, other members of the swarm (which are geographically dispersed) can predictively/proactively move into position to 1) maximize their probability of being able to detect and pursue the malicious UAV at a later time, and 2) maximize their individual tracking times if and when the malicious UAV enters their detection zone. This, of course, requires communication of the current malicious UAV trajectory between networked members of the swarm. A simulation of a sample tracking scenario is presented which quantifies the gain achieved by predictively and dynamically positioning pursuing UAVs to increase the probability that the malicious UAV is within the detection zone of at least one pursuing UAV at any arbitrary time. The gain is significant and ultimately allows a smaller swarm to be deployed for effective tracking. |
Keywords | UAV, drone, communication, predictive tracking |
ANZSRC Field of Research 2020 | 460609. Networking and communications |
400702. Automation engineering | |
400703. Autonomous vehicle systems | |
400608. Wireless communication systems and technologies (incl. microwave and millimetrewave) | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | School of Mechanical and Electrical Engineering |
School of Sciences | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q645w/predictive-tracking-of-a-high-capability-malicious-uav
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