关键词: 近距空战, 智能决策, 深度强化学习, 人机对抗, 飞行试验

Abstract: The air combat intelligent decision-making will greatly change the form of wars. Deep reinforcement learning pro-vides a promising way of decision-making to explore and exploit the potential of unmanned aircrafts. It is an important technical paradigm to realize the intelligent decision-making in air combat. However, reports on its engineering implementation are rare. Aiming at the practical implementation of the maneuver intelligent decision-making based on deep reinforcement learning in the one-to-one fighters' close-range air combat, an online deep neural network decision-making model suitable for application is developed. The control scheme that tracks the transformed guidance commands with the flight control law is proposed. The corresponding software and hard-ware architecture are realized and the human-machine combat flight test is carried out, which realizes the transfer from the virtual simulation to the real flight in intelligent air combat. It is shown that based on the maneuver decision-making and control concept developed in this paper, the intelligent unmanned aircraft makes logical maneuver decisions and it occupies the advantageous situation quickly by maneuver when combatting the human "pilots". The flight test results demonstrate the potential application of the deep neural network intelligent decision-making machine in the air combat.

Key words: Close-range air combat, Intelligent decision-making, Deep reinforcement learning, Human-machine combat, Flight test