Lower bounds on the mean square error (MSE) play an important role in evaluating the
direction-of-arrival (DOA) estimation performance. Among numerous bounds for DOA …

Sparse arrays are known to achieve an increased number of degrees-of-freedom (DOFs) for
direction-of-arrival (DOA) estimation, where an augmented virtual uniform array calculated …

In this paper, we address the problem of joint direction-of-arrival (DoA) and range estimation
using frequency diverse coprime array (FDCA). By incorporating the coprime array structure …

In this letter, we address the problem of direction finding using coprime array, which is one of
the most preferred sparse array configurations. Motivated by the fact that non-uniform …

Conventionally, mixed near-field (NF) and far-field (FF) source localization is performed
using a symmetric uniform linear array (ULA). Recently, two symmetric nonuniform linear …

In this letter, we develop a coarray interpolation method for direction-of-arrival (DOA)
estimation using the coprime electromagnetic vector-sensor (EMVS) array. Firstly, we derive …

In this letter, we develop an effective algorithm for direction-of-arrival (DOA) estimation of
coherent sources with coprime arrays. Firstly, we generate a virtual uniform linear array …

Existing tensor-based coherent direction-of-arrival (DOA) estimation methods adopting
spatial smoothing to decorrelate the coherent tensor statistics usually lead to a poor …

To achieve fast and accurate two-dimensional (2D) direction of arrival (DOA) estimation, a
novel deep ensemble learning method is presented in this paper. First, a convolutional …

Most existing methods for mixed far-field (FF) and near-field (NF) sources localization are
based on uniform linear arrays (ULAs) or some special sparse linear arrays (SLAs) such as …