The rapid development of Unmanned Aerial Vehicle (UAV) swarms poses a significant challenge to traditional defense systems. This paper proposes and simulates a novel "Spider Web"UAV defense self-organizing detection network system. Its core idea is to utilize Ant Colony Optimization (ACO) algorithms to guide a defensive UAV swarm for efficient self-organized patrol and detection. The system constructs a multi-layered defense area centered on a protected target, including a core defense zone and a dynamically scalable warning zone. Defensive UAVs autonomously fill "gaps"in the detection network by sensing and responding to changes in virtual "pheromones,"enabling rapid response to intruding threats [1]-[15]. © 2025 IEEE.
Original languageEnglish
Pages434-439
Number of pages6
DOIs
StatePublished - 2025
Event7th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA) - Lipetsk, Russian Federation
Duration: 12 Nov 202514 Nov 2025

Conference

Conference7th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA)
Country/TerritoryRussian Federation
CityLipetsk
Period12/11/2514/11/25

    Research areas

  • Ant Colony Optimization, Dynamic Detection, Path Planning, Self-Organizing Network, Simulation, Spider Web Mode, UAV Swarm Defense, Aircraft detection, Antennas, Learning systems, Motion planning, Network security, Swarm intelligence, Unmanned aerial vehicles (UAV), Aerial vehicle, Ant colonies, Colony optimization, Dynamic detection, Self-organising, Self-organizing network, Spider web, Spider web mode, Unmanned aerial vehicle swarm defense, Web mode, Ant colony optimization

ID: 150944276