Efficient parameter estimation of partially polarized electromagnetic waves

The paper considers the problem of statistically efficient estimation of the parameters of partially polarized electromagnetic (EM) waves with a uniform linear array of crossed dipoles. Previous research considered only completely polarized EM waves. The authors consider the maximum likelihood (ML) estimation of partially polarized wave parameters, in particular, the incident angles and the degrees of polarization. They present a computationally efficient large-sample ML estimator that avoids the multidimensional search over the parameter space, which is required by the exact ML estimator. They also show how to deal with the cases where some of the incident waves are known or are considered to be completely polarized. Finally, some numerical examples comparing the performance of the estimators with their theoretical statistical performance in a variety of scenarios are presented