Decentralized Unmanned Aerial Vehicle Swarms: Taxonomy, Analytical Resilience Models, and Interference Mitigation Strategies

<jats:p>Decentralized swarms of unmanned aerial vehicles represent a revolutionary technology with various applications, but so far there are no systemic analytical approaches that combine technical, tactical, and ethical aspects. This paper presents a systematic review of 47 publications from IEEE Xplore, Scopus, and Web of Science (2018–2026), developing original analytical models for swarm deployment. A taxonomy of three architectural types (centralized, hierarchical, decentralized) with quantitative resilience assessment shows decentralized swarms maintain effectiveness with up to 30% agent loss, versus 5% for centralized. An analytical J/S model evaluates communication channel vulnerability to electronic warfare, while a grid weight model wi(t+1)=wi(t)+αdi(t)−βλwi(t) with threshold wth=10 enables decentralized targeting without a single point of failure. Comparative analysis of MANET and DTN protocols reveals latency, reliability, and power trade offs, justifying a hybrid scheme for combat conditions. Economic analysis demonstrates cost exchange ratios reaching 1:1000, and computing infrastructure assessment shows a 100 UAV swarm requires ≈2 PetaFLOPS with 70% ground and 30% onboard distribution using NPUs. Findings provide practical recommendations for swarm architecture selection, hybrid communication protocols, specialized autopilot modes, automated ground infrastructure, and mandatory human in the loop confirmation for critical targeting decisions. Future research priorities include experimental validation, integration with large language models, and cyber security assurance.</jats:p>