Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/32953
Title: A Simulation Study of a Self-organizing "spider Web" UAV Defense Detection Network Based on Ant Colony Optimization
Authors: Skvortsova, O. I.
Скворцова, О. И.
Keywords: UAV swarm defense;Ant Colony Optimization;Dynamic detection;Path planning;Self-organizing network;Simulation;Spider web mode
Issue Date: 2025
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Malafeyev O., Zaitseva I., Zhang K., Ostapenko E., Skvortsova O., Kolesov D. A Simulation Study of a Self-organizing "spider Web" UAV Defense Detection Network Based on Ant Colony Optimization // Proceedings - 2025 7th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2025. - 2025. - pp. 434 - 439. - DOI: 10.1109/SUMMA68668.2025.11302237
Series/Report no.: Proceedings - 2025 7th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2025
Abstract: 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].
URI: https://dspace.ncfu.ru/handle/123456789/32953
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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