Polarimetric SAR Imagery Target CFAR Detection Analytical Algorithm with Wishart Distribution
ZHANG Jia-feng1, ZHU Bo2, ZHANG Peng1, WANG Ming-chun1, LIU Tao1
1. School of Electronic Engineering, Naval University of Engineering, Wuhan, Hubei 430030, China;
2. Institute of Information and Technology, Naval Academy of Armament, Beijing 102200, China
Abstract：The equivalent number of looks (ENL) is a key parameter that affects the constant false alarm rate (CFAR) detection performances in polarimetric synthetic aperture radar (PolSAR) imageries.At present,the estimated value of the ENL mostly is not an integer,resulting that existing CFAR detection algorithms are no longer applicable.To solve this problem,a new analytical CFAR algorithm of target detection is proposed in PolSAR imageries.Firstly,the probability density function (PDF) of multi-look polarimetric whitening filter (MPWF) metric is derived based on Wishart distribution assumption;Secondly,the analytical expression of CFAR detection threshold with respect to the ENL is obtained by integrating the PDF of MPWF metric;Finally,the CFAR detection performances of the new algorithm are compared with other CFAR detection algorithms via simulation data and AIRSAR measured data.The results show that the real false alarm probability in the new algorithm is the closest to the given constant false alarm probability,which better guarantees the hypothesis of the constant false alarm probability in the CFAR detection.
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2018, Vol. 46 
