The tracking and recognition of the three-dimensional trajectories of cooperative target points is the key to the estimation of the position and attitude of multi-aircraft in an indoor environment. Therefore, a multi-target three-dimensional trajectory tracking and recognition algorithm based on time and space consistent conditions was proposed. This method included two parts of motion trajectory tracking and recognition. For the three-dimensional trajectory tracking of cooperative target points, a data association method based on the consistency of the displacement vector of the moving target was proposed. This method first used the data association probability calculated by the motion smoothness assumption. Combined with the Hungarian algorithm to solve the target data association relationship, and then the three-dimensional trajectory tracking of cooperative target points under the Bayesian filter framework was realized. The three-dimensional trajectory recognition of cooperative target points was divided into two parts: the rank of the motion trajectory Hankel matrix to realize the coarse recognition of the motion trajectory, and the Hausdorff distance between the motion trajectories to realize the fine recognition of the motion trajectory. Eventually the trajectory recognition and registration of each aircraft was realized. Under the experimental conditions of computer vision measurement method and 2 m×2 m×2 m measurement space, the results show that the proposed multi-target tracking algorithm has a three-dimensional trajectory tracking error of less than 4 mm (3σ), and the trajectory recognition accuracy rate is 100%. Therefore, the proposed algorithm can effectively realize the tracking and recognition of the three-dimensional trajectory of cooperative target points on multi-aircraft.