Abstract
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.
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