A Novel CFAR Detection Algorithm in K-Distributed Clutter for Polarimetric SAR Imagery
ZHANG Jia-feng1,2, ZHANG Peng1, WANG Ming-chun1, LIU Tao1
1. School of Electronic Engineering, Naval University of Engineering, Wuhan, Hubei 430030, China;
2. No. 92118 Unit of PLA, Zhoushan, Zhejiang 316000, China
Abstract：In the case that the clutter of the polarimetric synthetic aperture radar (PolSAR) imagery follows K distribution,the existing constant false alarm rate (CFAR) detection algorithms based on multi-look polarization whitening filter (MPWF) cannot be applied to the condition that the equivalent number of looks is a non-integer.To solve the problem,a CFAR detection algorithm with analytical false alarm probability expression is proposed.After introducing the Gamma distribution texture under the product model,the probability distribution function (PDF) of the MPWF metric is integrated to obtain its cumulative distribution function (CDF),and then the analytical form of the false alarm probability with respect to the detection threshold is obtained.The simulation results show that the new algorithm has a good false alarm fitting effect.In addition,when the target clutter ratio (TCR) is large,the new algorithm has a higher detection probability.Otherwise,the detection probability is lower than the existing algorithm.It is worth pointing out that the current false alarm probability expression of multi-look polarization matched filter (MPMF) under K distribution is wrong,so the current detection algorithm based on MPMF detection metric is modified and the correct expression of the false alarm probability is derived.
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2019, Vol. 47 
