Abstract
The problem of direction of arrival estimation of multiple sources in noise with unknown covariance is considered. The noise is modeled as a spatial autoregressive process with unknown parameters. An approximate maximum likelihood estimator (MLE) of the signal and noise parameters is derived. It requires numerical maximization of a compressed likelihood function over the unknown arrival angles. Analytical expressions for the MLEs of the signal covariance and the autoregressive (AR) parameters are given.<>

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