Abstract:Accurate aircraft detection and tracking methods can help improve a country's military strength, but there are few effective tracking methods for small target aircraft. The object tracking methods based on deep learning have better performance than traditional methods. Therefore, in view of the poor performance of traditional methods for small target tracking, this paper proposes an aircraft tracking method based on YOLOv3 and Kalman filter to obtain better performance. The improved algorithm first detects the target through the improved YOLOv3 algorithm, after that, the Kalman filter is used to predict the aircraft's trajectory, and the Hungarian algorithm is used for data association. Experimental results show that the detection performance of the algorithm for small-scale aircraft is improved by nearly 5% compared with the traditional YOLOv3, and the tracking effect of the aircraft has high accuracy and real-time performance, which has high military application value.