Abstract: To solve the problem of incomplete information in air combat, research of offensive and defensive game strategy of UAV (Unmanned Aerial Vehicle) based on an improved sparrow algorithm is conducted. By analyzing the air combat information of the enemy and ourselves, the offensive and defensive game model is established in the case of determining the air combat situation advantage function, air combat performance advantage function and profit function of the enemy and ourselves. Then, combining the game payout function given by the game model and calculating the payout matrix of the enemy and ourselves, an improved sparrow algorithm based on reverse learning is proposed to solve the Nash equilibrium solution of the offense and defense game between the enemy and ourselves. Finally, the feasibility and the effectiveness of the proposed algorithm are verified through simulations. This scheme can preliminarily solve the problem of incomplete information encountered in the process of air combat confrontation.

Key words: unmanned aerial vehicle (UAV),  , attack and defense games,  , incomplete information,  , improved sparrow algorithm,  , reverse learning