Signal subspace algorithms for direction of arrival estimation in the presence of a class of unknown noise fields

The authors propose a technique to compute signal bearings for the situation when the desired signal is corrupted by additive noise with unknown covariance. The noise covariance matrix is assumed to be a banded symmetric Toeplitz matrix. This algorithm eliminates the need for the evaluation of eigenvalues and eigenvectors. The algorithm is also computationally very efficient, since it requires the use of a simpler orthogonal decomposition, i.e. only the Householder decomposition. The number of computations required to perform this decomposition is of the order of O(2N³/3), while the eigendecomposition requires O(N⁴) computations