  We consider the optimal transport problem between multivariate Gaussian
stationary stochastic processes. The transportation effort is the variance of
the filtered discrepancy process. The main contribution of this technical note
is to show that the corresponding solution leads to a weighted Hellinger
distance between multivariate power spectral densities. Then, we propose a
spectral estimation approach in the case of indirect measurements which is
based on this distance.
