The Development of Rule-based AI Engagement Model for Air-to-Air Combat Simulation

Since the concept of Manned-UnManned Teaming(MUM-T) and Unmanned Aircraft System(UAS) can efficiently respond to rapidly changing battle space, many studies are being conducted as key components mosaic warfare environment. In this paper, we propose a rule-based AI engagement model based on Basic Fighter Maneuver(BFM) capable Within-Visual-Range(WVR) air-to-air combat simulation environment in which human pilots participate. order develop that pilot fighter with 6-DOF dynamics model, tactical manuals experience were configured knowledge specifications modeled behavior tree structure. Based this, improved shortcomings existing air models. The proposed not only showed 100 % winning rate pilots, but also visualized decision-making processes such situations maneuvering behaviors real time. We expect results research will serve basis for development various AI-based models simulators training embedded software test platform fighter.