Decision making in autonomous air combat: Review and prospects

In the Autonomous Air Combat (AAC) technique, the aircraft is expected to autonomously perform situational perception, decision making, and control execution in the combat, among which decision making is the core of the AAC technique. This paper reviews the state of the art decision-making methods in the AAC technique by dividing them into three groups, i.e. mathematics-based, knowledge-encoded, and learning-driven methods. We list the representative techniques in each group, discussing both the weaknesses and strengths. We point out that the future development of AAC should root in the traditional mathematical approaches, while also incorporating novel techniques, e.g. machine learning and artificial intelligence. Both challenges and potential solutions to this proposal are listed. This paper delivers a brief analysis of past experiences and future prospects of the AAC development, hoping to promote the academic research and engineering applications. © 2020, Beihang University Aerospace Knowledge Press. All right reserved.