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

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.