  This paper adresses the statistical performance of subspace DoA estimation
using a sensor array, in the asymptotic regime where the number of samples and
sensors both converge to infinity at the same rate. Improved subspace DoA
estimators were derived (termed as G-MUSIC) in previous works, and were shown
to be consistent and asymptotically Gaussian distributed in the case where the
number of sources and their DoA remain fixed. In this case, which models widely
spaced DoA scenarios, it is proved in the present paper that the traditional
MUSIC method also provides DoA consistent estimates having the same asymptotic
variances as the G-MUSIC estimates. The case of DoA that are spaced of the
order of a beamwidth, which models closely spaced sources, is also considered.
It is shown that G-MUSIC estimates are still able to consistently separate the
sources, while it is no longer the case for the MUSIC ones. The asymptotic
variances of G-MUSIC estimates are also evaluated.
