There is a problem of the poor applicability of clutter models under high resolution with the existing constant false alarm rate (CFAR) detection methods in polarimetric synthetic aperture radar (SAR) imageries. To solve the problem

a CFAR detection method with an analytical expression for the false alarm rate is proposed. Firstly

the probability density function (PDF) of the polarization whitening filter (PWF) metric is derived based on product model combining the hypothesis of the Fisher distribution texture. Secondly

the PDF of the PWF metric is integrated

and the analytical expression of the false alarm rate

with respect to the detection threshold is obtained. The process of the proposed CFAR detection method is also designed. Finally

the CFAR detection performances of the proposed method are compared via airborne SAR (AIRSAR) real data with the existing detection methods

such as the two-parameter CFAR (2P-CFAR) detector and the detection methods based on K distribution

G

0

distribution and Wishart distribution. The results show that the proposed method can detect the targets effectively

and the robustness of the method is strong. Compared with other detection methods

the figure of merit (FoM) of the proposed method is on average higher than 32.66%.