Polarization target detection algorithm based on instantaneous Stokes sub-vector

Firstly, the statistics of random polarized wave´s instantaneous Stokes sub-vector is analyzed and its probability density function (PDF) is obtained. Secondly, the target detection problem is skillfully translated into the detection problem of three equivalent polarization signals. Thereby, a novel fusion detection algorithm is presented based on the difference statistical distribution of Stokes sub-vector between targets and clutters. Experimental results show that no matter the target is random polarization or invariable polarization, the algorithm is effective. Its performance can be comparative to that of the optimal polarization detector (OPD) and better than that of the polarization white filtering detector (PWF). Considering variable conditions of polarimetric measurements, it can be used more widely than the optimal polarization detector