On direction finding with unknown noise covariance
B. Friedlander, A.J. Weiss · 2002
A class of direction finding methods which operate in the presence of correlated noise with an unknown covariance matrix is presented. The approach is based on joint estimation of the directions of arrival and the parameters of a model for the noise covariance matrix, using a maximum likelihood estimator, its suboptimal version or other methods. Formulas for evaluating the maximal number of identifiable noise parameters are also derived. Using the Cramer Rao bound we study the degradation in DOA estimation accuracy due to the estimation of the noise parameters.>