Abstract: In the mobile edge computing scenario, the MEC processor, which provides mobile devices with the opportunity of unloading, is installed on the unmanned aerial vehicle (UAV) to help users' devices (UES) in the coverage area unload their tasks, and then the calculation results are returned. The UAV determines the hovering position and height in the service area according to the principle of the shortest distance. Considering the limited computing resources and energy of each UAV, this paper aims to price the resources in the case of limited resources. The revenue model of users and servers was given, and it was proved that the revenue function of users was convex. Stackelberg game was used to determine the offload mobility and final resource pricing of each user iteratively. The simulation results show that compared with the existing methods, the server revenue and the total system revenue are significantly improved, but the average task energy consumption and average delay are sacrificed.