Synthesis of optimal algorithms for useful signal selection in presence of background noise with using polarization distinctive features

摘要

Optimal algorithms for polarization-doppler selection of movable and immovable objects noised by reflection from lengthy sources are synthesized with the use of the maximum likelihood principle. It is shown that these algorithms are adaptive and based 9n 6ptimum estimation data for elements of a covariance (polarization) matrix.