Dynamic Target Ammunition Assignment Model for Unmanned-air-vehicles Anti-ship Combat

Unmanned-air-vehicles (UAVs) cooperation has unique operational advantages in cooperative operation. Based on the factors such as target tactical value and formation defense advantage, a dynamic defense threat mathematical model of target fleet was established for multi-target allocation of UAV group. Based on the traditional ant colony algorithm, by improving its search mechanism and pheromone update range, a random ant colony (RRSACS) search algorithm based on pheromone range constraints was proposed. Using 12 UAVs against five ships, one batch of penetration and two penetration modes, the static and dynamic defense capabilities of ship formation were simulated and analyzed to verify the effectiveness of the model. The results show that the local optimal solutions of UAV penetration target fleet model in static environment and dynamic environment are 4.221 and 4.312 respectively. The target fleet dynamic defense model can truly simulate the fleet confrontation environment and reflect the defense space and cooperative advantage of the fleet in the process of actual combat. Under the same conditions (population number, pheromone concentration and battle wave), compared with the traditional ant colony algorithm, the improved RRSACS ant colony algorithm can reduce the allocation time of 50 s and improve the operation efficiency.