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CFAR Ship Detection in Nonhomogeneous Sea Clutter Using Polarimetric SAR Data Based on the Notch Filter

机译:基于陷波滤波器的极化SAR数据在非均匀海杂波中的CFAR舰船检测

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Synthetic aperture radar (SAR) ship detection is an important research topic in the field of maritime applications. The geometrical perturbation-polarimetric notch filter (GP–PNF) was recently proposed to be a promising tool and its usefulness in exploiting polarimetric SAR information for ship detection was demonstrated. The work in this paper is devoted to developing a statistical model of the filter in nonhomogeneous sea clutter to achieve constant false alarm rate (CFAR) detection based on the model. First, within the framework of a multiplicative model, the reciprocal of the gamma distribution is used to describe the texture component of sea clutter in nonhomogeneous background. As a result, a statistical model of the GP–PNF is analytically derived and found suitable for sea clutter scenes with a wide range of homogeneity. Second, we theoretically demonstrate that CFAR detection using GP–PNF is unrelated to the parameter in the original GP–PNF. Therefore, a simplified version of the GP–PNF is given. Third, the CFAR threshold of the simplified filter is mathematically derived. Experiments performed on measured L-band ALOS-PALSAR and C-band RADARSAT-2 SAR data verify the good performance of the developed statistical model and demonstrate the usefulness of the CFAR detection based on the simplified filter.
机译:合成孔径雷达(SAR)舰船检测是海事应用领域的重要研究课题。最近,提出了几何扰动-极化陷波滤波器(GP-PNF)是一种有前途的工具,并证明了其在利用极化SAR信息进行船舶检测中的有用性。本文的工作致力于建立非均匀海杂波滤波器的统计模型,以基于该模型实现恒定的误报率(CFAR)检测。首先,在乘法模型的框架内,伽马分布的倒数用于描述非均匀背景下海杂波的纹理成分。结果,通过分析得出了GP–PNF的统计模型,发现该模型适合于具有广泛同质性的海杂波场景。其次,我们从理论上证明使用GP-PNF进行CFAR检测与原始GP-PNF中的参数无关。因此,给出了GP-PNF的简化版本。第三,从数学上推导简化滤波器的CFAR阈值。对测得的L波段ALOS-PALSAR和C波段RADARSAT-2 SAR数据进行的实验证明了开发的统计模型的良好性能,并证明了基于简化滤波器的CFAR检测的有用性。

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