Benefiting from rapid development of imaging sensor technology, modern optical technology, and a high-speed computing chip, the star tracker's accuracy, dynamic performance, and update rate have been greatly improved with low power consumption and miniature size. The star tracker is currently one of the most competitive attitude measurement sensors. However, due to restrictions of the optical imaging system, difficulties still exist in moving star spot detection and star tracking when in special motion conditions. An effective star tracking method based on optical flow analysis for star trackers is proposed in this paper. Spot-based optical flow, based on a gray gradient between two adjacent star images, is analyzed to distinguish the star spot region and obtain an accurate star spot position so that the star tracking can keep continuous under high dynamic conditions. The obtained star vectors and extended Kalman filter (EKF) are then combined to conduct an angular velocity estimation to ensure region prediction of the star spot; this can be combined with the optical flow analysis result. Experiment results show that the method proposed in this paper has advantages in conditions of large angular velocity and large angular acceleration, despite the presence of noise. Higher functional density and better performance can be achieved; thus, the star tracker can be more widely applied in small satellites, remote sensing, and other complex space missions.