Aiming at the problems of less target feature information and low contrast between foreground and background in satellite video, this study proposes a target tracking method integrating motion information and attention mechanism based on SiamCAR. First, the motion excitation and channel attention modules are introduced to enhance the target feature extraction information. Then, adjacent frames are regarded as new templates and added to the network to form a triple network and supplement template information. Finally, the Kalman filter algorithm is added to predict the target’s trajectory, and a prediction template is introduced to the network to construct a quadruple network and increase the motion information of the target. In addition, 10 sets of data in the SatSOT satellite video data set are selected for testing. The experimental results show that compared with those of the SiamCAR network, the tracking accuracy and success rate of the improved algorithm are increased by 6% and 6.2%, respectively.