  In this paper, an approach of estimating signal parameters via rotational
invariance technique (ESPRIT) is proposed for two-dimensional (2-D)
localization of incoherently distributed (ID) sources in large-scale/massive
multiple-input multiple-output (MIMO) systems. The traditional ESPRIT-based
methods are valid only for one-dimensional (1-D) localization of the ID
sources. By contrast, in the proposed approach the signal subspace is
constructed for estimating the nominal azimuth and elevation
direction-of-arrivals and the angular spreads. The proposed estimator enjoys
closed-form expressions and hence it bypasses the searching over the entire
feasible field. Therefore, it imposes significantly lower computational
complexity than the conventional 2-D estimation approaches. Our analysis shows
that the estimation performance of the proposed approach improves when the
large-scale/massive MIMO systems are employed. The approximate Cram\'{e}r-Rao
bound of the proposed estimator for the 2-D localization is also derived.
Numerical results demonstrate that albeit the proposed estimation method is
comparable with the traditional 2-D estimators in terms of performance, it
benefits from a remarkably lower computational complexity.
