Performance Evaluation for Tracking a Malicious UAV using an Autonomous UAV Swarm

Paper


Arnold, Christopher and Brown, Jason. 2020. "Performance Evaluation for Tracking a Malicious UAV using an Autonomous UAV Swarm." 11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON 2020). New York City, United States 28 - 31 Oct 2020 Piscataway, United States. https://doi.org/10.1109/UEMCON51285.2020.9298062
Paper/Presentation Title

Performance Evaluation for Tracking a Malicious UAV using an Autonomous UAV Swarm

Presentation TypePaper
AuthorsArnold, Christopher (Author) and Brown, Jason (Author)
Journal or Proceedings Title11th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON 2020)
Number of Pages6
Year2020
Place of PublicationPiscataway, United States
ISBN9781728196565
Digital Object Identifier (DOI)https://doi.org/10.1109/UEMCON51285.2020.9298062
Web Address (URL) of Paperhttps://ieeexplore.ieee.org/abstract/document/9298062
Conference/Event11th 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.

KeywordsSwarm, UAV, autonomous, tracking, OMNeT++
ANZSRC Field of Research 2020460609. Networking and communications
400702. Automation engineering
460608. Mobile computing
400703. Autonomous vehicle systems
Byline AffiliationsSchool of Mechanical and Electrical Engineering
Institution of OriginUniversity of Southern Queensland
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