Performance Evaluation for Tracking a Malicious UAV using an Autonomous UAV Swarm
Paper
Paper/Presentation Title | Performance Evaluation for Tracking a Malicious UAV using an Autonomous UAV Swarm |
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Presentation Type | Paper |
Authors | Arnold, Christopher (Author) and Brown, Jason (Author) |
Journal or Proceedings Title | 11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON 2020) |
Number of Pages | 6 |
Year | 2020 |
Place of Publication | Piscataway, United States |
ISBN | 9781728196565 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/UEMCON51285.2020.9298062 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/abstract/document/9298062 |
Conference/Event | 11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON 2020) |
Event Details | 11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON 2020) Event Date 28 to end of 31 Oct 2020 Event Location New York City, United States |
Abstract | Recent instances of malicious Unmanned Aerial Vehicles (UAVs) causing service disruption or damage to critical infrastructure has prompted research into methods of mitigating and deterring such nefarious activities. One such countermeasure is to use a swarm of UAVs to track the malicious UAV back to its origin. In this paper, we evaluate different methods of swarm formation for the purposes of malicious UAV tracking via a bespoke OMNeT++ simulation. The simulation also evaluates the effect of the number of UAVs in the swarm, as well as the evasiveness of the malicious UAV in terms of its flight capabilities and flight path. The results demonstrate that encirclement type swarm formations such as Surround and Cone, in which the malicious UAV is surrounded by the swarm, perform better than a follow type swarm formation in their ability to continue to track the malicious UAV. |
Keywords | Swarm, UAV, autonomous, tracking, OMNeT++ |
ANZSRC Field of Research 2020 | 460609. Networking and communications |
400702. Automation engineering | |
460608. Mobile computing | |
400703. Autonomous vehicle systems | |
Byline Affiliations | School of Mechanical and Electrical Engineering |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q60q9/performance-evaluation-for-tracking-a-malicious-uav-using-an-autonomous-uav-swarm
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