The trajectory prediction of infrared moving target is widely used in military and civilian fields such as monitoring and space-based remote sensing detection. When the relative velocity of the target is much higher, influenced by the fixed readout rate and integration time, the target trajectory points obtained by the traditional full field of view imaging information acquisition method are sparse, and it’s difficult to meet the accuracy requirements of target trajectory predication. To address this problem, an information acquisition method for fast moving targets based on dynamic windowing(DW) was proposed. The observation area was first imaged with full field of view, and after capturing the moving target, the target and its neighbors were imaged with a window to increase the frame rate. The discriminant matrix was obtained by analyzing the influence of the radiation characteristics of the detection scene on the working parameters of the system, and the dynamic adjustment of the window opening parameters was realized and the density of target trajectory points was enhanced. Finally, the window openning position was updated using the target trajectory prediction results to achieve the full-field coverage monitoring of a single target. The experimental results show that for the mid-wave infrared demonstration system, the method increases the target trajectory point density by 16 times and the system trajectory prediction accuracy by 2.6 times compared with the full field of view imaging information acquisition method. And the required data transmission bandwidth is reduced by 25%. This study can provide useful reference for the design of intelligent infrared sensing systems.