Classical methods of DOA estimation such as the MUSIC algorithm are based on estimating
the signal and noise subspaces from the sample covariance matrix. For a small number of …

This paper provides a new analytic expression of the bias and RMS error (root mean
square) error of the estimated direction of arrival (DOA) in the presence of modeling errors …

Usually, direction-of-arrival (DOA) estimators are derived under the assumption of uniform
white noise, whose covariance matrix is a scaled identity matrix. However, in practice, the …

The uniform white noise assumption is one of the basic assumptions in most of the existing
direction-of-arrival (DOA) estimation methods. In many applications, however, the …

Although traditional subspace direction of arrival (DOA) algorithms enable super-resolution,
the algorithm performance declines sharply when the number of sources is incorrectly …

Based on the investigation to classical DOA algorithm (MUSIC and improved MUSIC), a
novel DOA estimation algorithm is proposed which makes full use of signal subspace and …

A novel real-valued root multiple signal classification (RV-root-MUSIC) algorithm for
estimating the direction-of-arrival (DOA) of multiple narrow-band signals is presented …

A modified MUSIC algorithm for DOA estimation was proposed in this paper. It weighted the
eigenvectors in the noise subspace which decreased the proportion of the eigenvectors of …

This paper presents a new computationally efficient method for direction-of-arrival (DOA)
estimation with arbitrary arrays. The total angular field-of-view is first divided into several …

A new algorithm involving sparse recovery is proposed to address the problem of direction-
of-arrival (DOA) estimation using weighted subspace fitting (WSF). The proposed algorithm …