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Aiming at the problem that the dynamic underwater target tracking and positioning process requires good real-time and robustness, a method of underwater dynamic target localization based on binocular vision is proposed. Firstly, the illumination component of the underwater image is extracted by fast guidance filtering, and then the two-dimensional gamma function is constructed and the parameters of the two-dimensional gamma function are adjusted by using the distribution characteristics of the illumination component, so as to realize the adaptive correction processing of the uneven illumination image. Secondly, the Kalman filter is used to predict the position of the target at the next moment, and the prediction space is used as the ROI region for image correction, which greatly reduces the running time of the algorithm, and then the target is masked in the HSV space, and the target is accurately located by the binocular positioning algorithm after recognition. Finally, compared with multi-scale Gaussian function and bilateral filtering algorithms, the proposed method has a significant improvement in running speed and high positioning accuracy in the positioning process, and the results show that the algorithm can meet the real-time and robustness requirements of underwater dynamic target tracking and positioning.