A new low-complexity parameters estimator for multiple two-dimensional (2D) domain incoherently distributed (ID) sources is presented. One 2D domain ID source is parameterized with four parameters, the central azimuth direction-of-arrival (DOA), azimuth angular spread, central elevation DOA and elevation angular spread. Based on the eigenstructure between the steering matrix and signal subspace, an average total least-squares via rotational invariance technique (TLS-ESPRIT) is used to estimate the central elevation DOA, and then a generalized multiple signal classification (GMUSIC) algorithm is derived to estimate the central azimuth DOA. Utilizing preliminary estimates obtained at a pre-processing stage, the angular spread parameters can be obtained by matrix transform. To estimate four-dimensional parameters, our algorithm only needs one-dimensional search. Compared with earlier algorithms, our method has lower computational cost. In addition, it can be applied to scenarios with multiple sources that may have different angular power densities. Finally, the Cram'er-Rao Lower bound (CRLB) for parameters estimation of 2D domain ID sources is also derived. Numerical simulations are carried out to study the performance of the suggested estimator.

A new low-complexity parameters estimator for multiple two-dimensional (2D) domain incoherently distributed (ID) sources is presented. One 2D domain ID source is parameterized with four parameters, the central azimuth direction-of-arrival (DOA), azimuth angular spread, central elevation DOA and elevation angular spread. Based on the eigenstructure between the steering matrix and signal subspace, an average total least-squares via rotational invariance technique (TLS-ESPRIT) is used to estimate the central elevation DOA, and then a generalized multiple signal classification (GMUSIC) algorithm is derived to estimate the central azimuth DOA. Utilizing preliminary estimates obtained at a pre-processing stage, the angular spread parameters can be obtained by matrix transform. To estimate four-dimensional parameters, our algorithm only needs one-dimensional search. Compared with earlier algorithms, our method has lower computational cost. In addition, it can be applied to scenarios with multiple sources that may have different angular power densities. Finally, the Cram'er-Rao Lower bound (CRLB) for parameters estimation of 2D domain ID sources is also derived. Numerical simulations are carried out to study the performance of the suggested estimator.