Fast adaptive eigenvalue decomposition: a maximum likelihood approach

A new adaptive subspace estimation algorithm is presented, based on the maximisation of the likelihood functional. It requires little computational cost and the particular structure of the algorithm ensures the orthonormality of the estimated basis of eigenvectors. Application to moving sources localization shows the very good behavior of the algorithm when applied to problems of practical interest.