The three-dimensional （3D） spectrum situation is a significant method to handle the issue of making full use of spectrum resources in the ground-air-space integrated information network. It characterizes the time-space-frequency distribution of the power spectrum density in 3D electromagnetic space. Hence， the communication system can implement a variety of applications such as spectrum prediction， spectrum decision， and spectrum management and control in a targeted manner. However， due to user deployment and other factors， the actual 3D spectrum situation is often discrete and incomplete. Therefore， this paper proposes a 3D spectrum situation completion algorithm based on generative adversarial networks （GANs）. Moreover， this paper proposes an improved GANs structure and data processing methods to decrease the completion error and the training time of the algorithm. Simulation results indicate that the proposed algorithm can effectively complete the 3D spectrum situation and outperform the conventional interpolation method in terms of completion accuracy.