The aircraft stability tracking is carried out for the pilot′s training mission.In order to solve the problems such as small target, complex weather environment and bird disturbance, an aircraft tracking measurement method based on deep learning and correlation filtering is proposed in this paper.Firstly, the backbone network is selected and the algorithm model of deep learning is established. Then, a reference model for the actual scene is obtained by using a large number of aircraft images. And the features detected by the model are combined with the correlation filtering to achieve the stable tracking effect of the aircraft and generate the missing distance of the target.According to the tracking information and missing distance, the laser is turned on and the laser ranging principle is used to measure the real-time range of the aircraft.Finally, an aircraft capture and tracking experiment based on the photoelectric theodolite is carried out to verify the validity and feasibility of the model and algorithm.The experimental results show that the target information obtained by deep learning and correlation filtering can be used to capture and track long-range aircrafts. It successfully eliminates the interference of complex environment and birds, and the stable tracking of aircraft realizes.