Direction finding using noise covariance modeling

We consider the problem of direction finding in the presence of colored noise whose covariance matrix is unknown. We show that the ambient noise covariance matrix can be modeled by a sum of Hermitian matrices known up to a multiplicative scalar. Using this model, we estimate jointly the directions of arrival of the signals and the noise model parameters. We show that under certain conditions, it is possible to obtain unbiased and efficient estimates of the signal direction. The Cramer-Rao bound is used as the principal analysis tool. Computer simulations using the maximum likelihood estimator provide a validation of the analytical results.<
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