In order to solve the target tracking problem in complex scenes such as target changes and nonuniform illumination of the scene, this paper proposes a target tracking algorithm based on dynamic adaptive correlation filtering in complex scenes. The algorithm first constructs a set of geometrically distorted target reference images, and then combines the constructed optimal templates for each graph based on the idea of the combined filter. At the same time, in order to avoid the need to prespecify the target expected position in the next frame, the algorithm uses a time seriesbased prediction mechanism to improve the tracking accuracy by considering the kinematics of the target. Finally, the algorithm is designed with a reinitialization mechanism to restart the system in the event of a system failure. The simulation results show that the proposed algorithm has better tracking accuracy and tracking efficiency than the existing ones, which verifies the effectiveness and feasibility of the proposed algorithm.