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A novel ship wake constant false alarm rate (CFAR) detection algorithm is proposed. The algorithm first detects all the ships and replaces the pixels' gray value of the detected ship with the gray mean value. Then, with the ship target's geometric center as the center, a square image with a certain length is got, and the image is subdivided into four subimages, where the gray intensity contrast of the wake to clutter in the subimage is enhanced. Normalized Hough transform is applied on every subimage, and the probability distribution function in the Hough domain of each subimage is modeled, which can be used for CFAR detection. Finally, the detection results of the subimages are fused to get the final detection. Using our algorithm, the signal-to-clutter ratio of the wake to clutter is enhanced, the ship's navigation direction can be extracted easily, and most importantly, CFAR detection is realized.