Operation utilized by air support of drones at a close range is currently a research focus.The path and target allocation of Unmanned Aerial Vehicles (UAVs) for multi target firepower strikes require optimization under conditions of complex battlefield environments, and the following factors, such as UAV flight altitude, different weapon mounts, target types and various indicators, threat cost in threat zones, and operational time cost, should be taken into account. A comprehensive target damage index is constructed to improve asymmetric strike effectiveness, and a threat zone security threshold is set to improve path effectiveness analysis. The total cost of the optimal trajectory is planned by adopting the Adaptive Weighted Particle Swarm Collaborative Optimization (APSCO) algorithm for a single drone and a single target, and the imbalanced task allocation scheme is completed by adopting the 0-1 programming method for multiple drones against multiple targets,providing decision support for the allocation of multiple unmanned aerial vehicles to multiple targets at a close range in performing air support tasks.