提出一种基于分块相位梯度算法(PGA)的多舰船尾迹合成孔径雷达(SAR)图像自动识别方法。首先在多结构形态学滤波和自适应阈值(OTSU)分割的基础上, 利用分块PGA算法消除运动舰船的位置偏移和像元模糊, 还原舰船实际信息; 利用改进的局部Hough变换对分块图像进行检测和识别, 根据识别出的尾迹坐标和角度反演运动舰船位置和航向信息。检测结果表明, 该算法可准确检测SAR图像中舰船的实际位置和航向, 识别准确度高, 抗干扰性强。

A Phase Gradient Algorithm(PGA) based algorithm for the automatic recognition of multiple ship wakes in Synthetic Aperture Radar(SAR) image is presented. Firstly, the center point of each ship image is extracted by using a combination algorithm of multiple-structure morphology filtering, the OTSU automatic segmentation and the clustering method. Then, the whole image is divided into sub-images which are chosen to be a square of appropriate size and the centers of sub-images are the detected points. As moving ships in SAR image always result in residual chirps in the azimuthally processed signals, the block-wise PGA is utilized to compensate the position offset and defocusing effect in each sub-image. Finally, an improved local Hough transform is proposed to detect the ship wake based on an inverse analysis of the detected wake's coordinate and angle, and the locations and the trajectories of each moving ship are obtained. The examples demonstrate that this algorithm can accurately recognize and restore the ships' actual trajectories and locations with high detectability and low false detection rate.