A method for the direction-of-arrival estimation of incoherently distributed sources

We consider the problem of estimating the nominal direction of arrival (DOA) of an incoherently distributed source. This problem is encountered due to the presence of local scatterers in the vicinity of a transmitter or due to signals propagating through a random inhomogeneous medium. Since the spatial covariance matrix has full rank for an incoherently distributed source, the performance of most high-resolution DOA estimation algorithms conceived under coherently distributed sources, as well as point source models, degrades when scattering is present. In addition, several DOA estimation techniques devised under a distributed source model require a high-dimensional nonlinear optimization problem. In this paper, we propose a novel method based on the conventional beamforming approach, which estimates the nominal DOA from a spatial maximum peak of the output power. The proposed method is computationally more attractive than the maximum likelihood (ML) estimator, although the performance degrades in comparison with the ML estimator, whose asymptotic performance is equivalent to the Cramer-Rao bound (CRB). We derive and compare the asymptotic performances of the proposed method and the redundancy-averaged covariance matching (RACM) method in the single-source case. The simulation results illustrate that the asymptotic performance of the proposed method is better than that of the RACM method.