Neural network air combat maneuver decision-making method based on particle swarm search

The invention relates to the technical field of air combat maneuver decision making, in particular to a neural network air combat maneuver decision making method based on particle swarm search, which comprises the following steps of: 1, establishing a kinematics and dynamics model of a red and blue air combat fighter; 2, establishing air combat situation dominant functions including an angle dominant function, a speed dominant function, a distance dominant function and a height dominant function; 3, optimizing an air combat maneuver decision by using a particle swarm algorithm; 4, generating an air combat two-party trajectory and maneuver decision database; 5, constructing a neural network and training the neural network; and 6, maneuvering decision making based on the neural network. The air combat maneuver decision provided by the invention has better superiority and rapidity. 本发明涉及空战机动决策技术领域，涉及一种基于粒子群搜索的神经网络空战机动决策方法，其包括以下步骤：一、建立红蓝双方空战战斗机运动学与动力学模型；二、建立空战态势优势函数，包括角度优势函数、速度优势函数、距离优势函数、高度优势函数；三、粒子群算法优化空战机动决策；四