Agent-based real-time simulation of target assignment and deployment strategies for counter-UAV defense in multi-drone threat scenarios

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Small unmanned aircraft systems are becoming a serious asymmetric threat to military facilities and critical infrastructure because they are inexpensive, maneuverable, and can be operated in coordinated groups. In multi-drone scenarios, counter-unmanned aerial vehicle defense requires rapid detection, target assignment, and engagement under time-varying conditions. This paper presents an agent-based real-time simulation model for evaluating target assignment rules and deployment strategies in multi-drone defense. Defense agents and incoming drones are modeled as individual agents updated at discrete time steps through movement, detection, candidate target generation, assignment, persistent engagement, probabilistic neutralization, and defense-line breach assessment. Sequential-based, distance-based, and threat-based assignment strategies are compared with random and Hungarian assignment as reference methods. Linear deployment and cluster-based distributed deployment are evaluated under identical conditions. In 1000 replications, distributed deployment with distance-based assignment reduced mean initial detection time from 84.00 to 63.47 s and mean neutralization time from 129.25 to 89.50 s. Defense success rate increased from 56.12% to 87.85%. The results indicate that counter-unmanned aerial vehicle defense performance depends on deployment geometry, assignment rule, persistent engagement, and probabilistic neutralization, not only on the number of defense agents.