An efficient clonal selection algorithm to solve dynamicweapon-target assignment game model in UAV cooperative aerial combat

The environment of UAV cooperative aerial combat is complex and changeable, with strong antagonism. Therefore, high accuracy and real-time are required. A multi-combat step UAV dynamic weapon-target assignment (DWTA) game model is established with the survival probability and weapons consumption factors for warring parties. Also the solving method of bimatrix game Nash equilibrium point is applied to the model. A solving method based on clonal selection algorithm is proposed. The algorithm considers both the diversity of population and the convergence speed. Simulation results show the Nash equilibrium solution obtained by the algorithm is more accurate, which ensures the real-time and efficiency.