基于散射相似性参数的全极化合成孔径雷达船只检测

Ship detection in POL-SAR Image Using Scattering Similarity Parameters

全极化合成孔径雷达(SAR)数据提供了丰富的散射信息,目前被广泛应用于海上船只目标的检测。本文首先利用一种方便有效的极化散射信息分析法-散射相似性参数统计分析了船只目标与海面的散射特性,重点分析了两者散射机制间的差异,并基于该差异提出了一个新的全极化SAR船只目标检测量(SSM),该检测量同时考虑了极化SAR数据的空间信息,有效提高了船海对比度。然后基于核密度估计提出了对检测量SSM的模型估计方法,结合恒虚警率(CFAR)检测方法实现了对船只目标的检测。利用RADARSAT-2全极化数据对本文的方法进行验证,并与典型的极化SAR船只目标检测方法比较,实验结果表明了本文方法对船只目标检测的有效性。

Ship detection plays an important role in the field of marine surveillance applications,such as fisheries management,search and rescue of vessels,and pollution monitoring.The synthetic aperture radar(SAR),due to the ability to image through cloud cover and independence of illumination,together with a fine spatial resolution,has became the key remote sensing tool to observe metallic targets at sea.Polarimetric SAR data contains abundant information about objects’scattering properties and they have been widely used in the research of ship detection in recent year.In this paper,we firstly utilize the scattering similarity parameters to investigate the differences of scattering mechanism between ship targets and sea surface,rather than the traditional polarization decomposition methods which have a complex calculation process,so the efficiency of the algorithm is improved.Then Based on the differences of scattering mechanism between the ship targets and sea surface,a novel ship target detection metric is proposed,which enhances the contrast between ship and sea effectively.The distribution function of the metric is modeled by using the method of kernel density estimation(KDE).Based on the statistical model,an automatic constant false rate(CFAR)detection is implemented.Experimental results conducted on RADARSAT-2 polarimetric SAR data and the comparative experiments demonstrate the effectiveness of the approach.