A Novel Ship Wake CFAR Detection Algorithm.pdf

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 8, NO. 4, JULY 2011 681 A Novel Ship Wake CFAR Detection Algorithm Based on SCR Enhancement and Normalized Hough Transform Ai Jiaqiu, Qi Xiangyang, Yu Weidong, Deng Yunkai, Liu Fan, Shi Li, and Jia Yafei Abstract—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. Index Terms—Constant false alarm rate (CFAR), normalized Hough transform (NHT), synthetic aperture radar (SAR), signal- to-clutter ratio (SCR) enhancement, ship wake detection. I. INTRODUCTION SYNTHETIC aperture radar (SAR) images have beenwidely used for fishing vessel detection and ship traffic monitoring [1]. Detection of ship wakes plays an important role in the estimation of moving-ship parameters, such as velocity and direction [2]. The most obvious characteristics of wake components are the linear features in a SAR image. Ship wakes appear as bright or dark lines that may keep for several kilometers behind the ship. It is well known that, when an image contains a straight line, its Radon transform exhibits a narrow peak if the line is brighter than its surrounding and a trough in the opposite case. Thus, t