基于贝叶斯优化算法的多机协同空战决策仿真

Multi-aircraft Cooperative Air Combat Decision-making Simulation Based on Bayesian Optimization Algorithm

多机协同空战是未来空空作战的重要形式,空战智能决策是空战研究的核心内容之一。根据多机协同的特点和空战智能决策的要求,首先构造多机协同空战的自主优势矩阵,并在此基础上依据多人冲突理论分别对和红蓝双方以及本机编队进行权重分配,由此得到多机协同空战的整体优势矩阵。然后给出了贝叶斯优化算法并应用此算法对该模型进行了优化分析,实现了多机协同空战的空战智能决策。仿真实例证明贝叶斯优化算法收敛速度快,能够收敛到全局最优解,能有效地解决多机协同空战中的空战决策问题。

Multi -aircraft cooperative air combat will be an important air- to -air combat format. The intelligent decision making is very important for air combat. According to the characters of air combat and the requirement of decision making, a self - determination advantage matrix of multi - aircraft cooperative air combat is built firstly. The weights of both sides and aircraft formation have been assigned based on conflict theory. The whole advantage matrix has been built based on the analysis. The Bayesian optimization algorithm is given out. The modeling has been optimized with Bayesian optimization algorithms and the multi - aircraft cooperative air combat decision - making is realized. Simulations have verified that the method could be used to solve the complex problem.