Translator Disclaimer
Presentation + Paper
4 May 2018 Responding to unmanned aerial swarm saturation attacks with autonomous counter-swarms
Laura Strickland, Michael A. Day, Kevin DeMarco, Eric Squires, Charles Pippin
Author Affiliations +
Autonomous unmanned aerial vehicles (UAVs) present an increasingly viable threat vector to the Defense com- munity. Existing response systems are vulnerable to saturation attacks of large swarms of low-cost autonomous vehicles. One method of reducing this threat is the use of an intelligent counter swarm with tactics, navigation and planning capabilities for engaging the adversarial swarm. Though previous studies exist that have produced libraries of basic fighter tactics employable by unmanned fixed-wing aircraft, we are aware of little prior work that explores close-in tactical engagements at a large scale (teams of at least size 10). We examine existing technologies that can be applied in fixed-wing swarm-versus-swarm engagement, including classic pursuit-evasion strategies and the application of Lanchester's laws for attrition calculations. Our recent studies center on lever- aging existing manned fighter combat doctrine, and on the benefits of collaboration. We consider experiments in close-air combat against adversaries capable of destroying aerial targets. The following work employs both a Monte Carlo analysis in a simulation environment to measure the effectiveness of several autonomous tactics, as well as an analysis of live flight experiments in swarm competitions with up to 10 vs. 10 scenarios.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Laura Strickland, Michael A. Day, Kevin DeMarco, Eric Squires, and Charles Pippin "Responding to unmanned aerial swarm saturation attacks with autonomous counter-swarms", Proc. SPIE 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, 106350Y (4 May 2018);

Cited by 4 scholarly publications.
Unmanned aerial vehicles


Neural networks

Defense and security

Back to Top