Air-combat decision-making for UAVs cooperatively attacking multiple targets

Considering a Beyond Visual Range (BVR) air combat scenario with a group of UAVs versus multiple hostile airborne targets, the decision-making problem for Cooperative Attack on Multiple Targets (CAMT) was investigated. First, the air combat threat situation was analyzed. Based on the principle of each target to be attacked at least being assigned one missile, the decision-making for CAMT was converted into a Missile-Target Assignment (MTA) optimization problem with the establishment of the attack effectiveness evaluation model. Then, a Simulated Annealing Genetic Algorithm (SAGA) was proposed to find out the optimal solution to the MTA problem. Finally, the final decision-making solution to the CAMT was derived from the obtained best missile-target assignment individual. Simulation results show that the proposed method is more effective than Genetic Algorithm (GA) to deal with the decision-making problem for CAMT.