Maximum likelihood direction finding of stochastic sources: a separable solution

A novel method is presented for maximum-likelihood direction-finding of stochastic sources which may be correlated. It is shown that the maximum-likelihood estimates of the angle parameters and unknown source covariance matrix may be obtained in a separable form, i.e. the angle parameters are obtained by maximizing a function of only the angle parameters. The source covariance matrix estimate is then obtained by an explicit formula. This results in a significant reduction of the dimensionality of the optimization problem to be solved compared to previous approaches based on direct maximization over all parameters. Computer simulation results are presented to demonstrate the performance of the proposed method