Aiming at the problem of low efficiency and low computational efficiency of local window K-distribution detection algorithm, a fast ship target detection algorithm based on local window K-distribution was proposed. Firstly, the original Synthetic Aperture Radar (SAR) image was selected by the iterative segmentation algorithm, and the potential target pixels in the original SAR image were removed according to the pre-selection. Then two-order and four-order integral images were calculated by using the sliding window at each pixel in the background images. Two-order and four-order moments of the K-distribution were calculated in the integral image in order to estimate the parameters of K-distribution. Secondly, the detection threshold was determined by solving the probability density function and the regions of interest were obtained according to the threshold. Finally, the false alarm target was detected by the method of fuzzy difference. The detection experiment using the real SAR image show that the running time of the algorithm is reduced by 50% compared with the local window K-distribution algorithm, and the quality factor is improved from 44.4% to 100%. The proposed algorithm not only ensures the real-time performance of the algorithm, but also improves the detection accuracy, and it has a certain application value in the automatic detection of SAR ship.