Aerial Combat Maneuver Decision Method for Unmanned Aerial Vehicles Based on Deep Reinforcement Learning

Unmanned Aerial Vehicle (UAV) close-range air combat environments are complex, with rapid changes in enemy aircraft maneuvers. Considering the difficulty of autonomous maneuvering decision-making for UAVs with six Degrees of Freedom (6DOF) in such environments, a hierarchical framework-based Proxima...

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Autor principal:	ZHANG Xiangrui, TAN Tai, LI Hui, ZHANG Jianwei, LI Bowen
Format:	Artigo
Idioma:	Inglês
Publicat:	Editorial Office of Computer Engineering 2025-12-01
Col·lecció:	Jisuanji gongcheng
Matèries:	unmanned aerial vehicle (uav)|proximal policy optimization (ppo) algorithm|six degrees of freedom|dual reward (dr)|hierarchical framework
Accés en línia:	https://www.ecice06.com/fileup/1000-3428/PDF/20251230.pdf
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