Predictive Maneuver for UAV Air Combat Confrontation Based on Game Theory

This paper presents a game theory-based decision-making algorithm for air combat maneuvers. The Dubins minimum achievable distance is introduced to replace the Euclidean distance, and situation assessment function is reconstructed as the utility function of the game model, providing a more accurate basis for maneuver decisions. To effectively handle different opponents UAVs, their autonomous maneuvering capabilities are graded, and corresponding strategies are formulated to enhance tactical flexibility. Meanwhile, the model predictive control method is used to optimize the real-time maneuver decisions based on the anticipated battlefield dynamics. Simulation results validate the effectiveness of the proposed method compared to existing methods.