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Robust Damage-Probability Optimization for Micro-UAV Attack–Detonation Control in Uncertain Environments
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DOI：10.1016/j.dt.2026.04.009.png)
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Abstract
En 中文
To address the issue of unreliable damage under environmental wind disturbances and high-mobility of the target conditions, a micro-miniature UAV (unmanned aerial vehicle) attack and detonation control method based on maximizing damage probability is proposed. A corresponding three-level system model of UAV-EFP warhead-target is established considering real-time velocity and position information of the UAV and the target. Based on this system model, a pair of damage probabilities for the current moment and next moment is derived and updated in real time. According to the relative trend of current and next moment damage probabilities, Wind-Resistant Dive Angle Optimization Algorithm (WR-DAO) and Evasion-Resistant Detonation Decision Optimization Algorithm (ER-DDO) are proposed to counteract uncertain disturbances, thereby theoretically maximizing the damage probability under non-ideal strong disturbance conditions. A simulation analysis was conducted on the entire flight and attacking process of a micro-miniature UAV equipped with EFP warhead and the proposed control module. Through the Monte Carlo method, it is verified that this approach can enhance the UAV's probability of damage by up to 68.4% with high robustness under complex operational conditions of environmental random wind disturbances up to 2.5° and target random velocity up to 5.5 m/s.
Keywords:
Nano-UAV
Probability of damage
Detonation control
Random disturbance
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