To achieve efficient and accurate multi-target search of a UAV swarm,and with consideration of the wide detection ranges of high-altitude UAVs and the strong maneuverability of low-altitude UAVs in the swarm,a novel cooperative target search method is proposed for heterogeneous UAV swarms,which can realize rapid regional search and accurate multi-target search according to the characteristics of different UAVs.First,the high-altitude UAVs use a region search algorithm based on digital pheromones to determine the targets presence area,which realizes area overlapping in short time.The low-altitude UAVs then proceeds to the target area guided by the high-altitude UAVs and use a precise search algorithm based on an Improved Wolf Pack Algorithm (IWPA) to accurately locate the target.To address the limitations of traditional wolf pack algorithm,such as insufficient information sharing,fixed step size,and susceptibility to local optima,improvements have been made by using particle swarm optimization,adaptive parameter adjustment,and differential evolution methods.These enhancements improve the algorithms global optimization capability and convergence speed.Simulation experiments demonstrate the effectiveness and superiority of the proposed model and method for target search tasks in complex environment.