With the development of UAV technology, multi-target tracking of UAV video has become one of the key technologies in the application of UAVs. Aiming at the problems of complex background interference, occlusion, variable viewpoint of height and angle in UAV multi-target tracking video, a multi-target tracking algorithm based on attention feature fusion is proposed. Firstly, the improved convolution attention module is introduced into the residual network, and a three-tuple attention feature extraction network is established. Then, a new feature fusion channel is added to the structure of the feature pyramid network, and a multi-scale feature fusion module is designed to enhance the model's ability to express the features of multi-scale targets. Finally, the target trajectory is obtained by target re-identification feature matching and bounding box matching. The simulation results show that the algorithm effectively improves the accuracy and robustness of the UAV multi-target tracking.