Abstract: Synthetic aperture radar (SAR) enables all-weather, day-and-night observation of high-value targets such as aircraft and ships, and can estimate their motion states. As the resolution of SAR systems improves, the synthetic aperture time becomes longer, leading to more severe range cell migration of moving targets in SAR images. Moreover, the time-varying nature of target velocities makes accurate velocity estimation of moving targets in high-resolution SAR images more challenging. To address this problem, this paper first derives the relationship between the range cell migration correction (RCMC) coefficient and the motion velocity of moving targets in SAR images, and analyzes the relationship between the equivalent pulse repetition frequency (PRF) of sub-aperture images and the PRF of the full-aperture image. Based on this, a segmented velocity estimation method for moving targets in high-resolution SAR images is proposed. The method first estimates motion direction of the target during RCMC. Then, sub-aperture segmentation is performed on the SAR image, and each sub-aperture image is refocused using the fractional Fourier transform to estimate the segmented azimuth velocity. Finally, by combining the estimated motion direction, the method achieves segmented velocity estimation of moving targets in high-resolution SAR images and obtains the real-time motion state of the target. Experimental results based on simulated data, as well as moving aircraft and ship targets from Umbra and Qilu-1 high-resolution SAR satellite data, validate the effectiveness of the proposed method.