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A covariance fitting algorithm for the estimation of direction-of-arrivals of multiple incident signals is addressed in this paper. The scheme takes advantage of the fact that the incident signals are spatially sparse. A previous study has presented the regularization parameters of the covariance fitting for a very large number of snapshots. In this paper, a strategy on how to determine the regularization constant of the covariance fitting for a general number of snapshots is presented. The strategy essentially exploits the norm of the noise covariance matrix. The proposed algorithm has been validated via numerical simulations.

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