Sparse array direction-of-arrival (DOA) estimation using tensor model has been developed
to handle multidimensional sub-Nyquist sampled signals. Furthermore, augmented virtual …

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

Augmented virtual arrays can be derived from the undersampled signals of sparse arrays for
underdetermined direction‐of‐arrival (DOA) estimation. However, it is difficult to exploit the …

In this paper, we propose a fiber-missing tensor completion-based method for direction-of-
arrival (DOA) estimation in sensor failure scenario, where the completion of a three …

Sparse arrays can provide superior resolution in direction‐of‐arrival (DOA) estimation with
limited number of sensors. Two‐dimensional (2D) arrays are fundamental to localization …

A tensor-based wideband direction of arrival (DOA) estimation method is proposed in this
paper. Virtual arrays are initially generated and extended into a unified ULA across all …

Existing matrix-based neural network for direction-of-arrival (DOA) estimation has to train a
large amount of parameters proportional to the length of vectorized signal statistics, resulting …

Compared to uniform arrays, non-uniform arrays can substantially increase the rank of the
channel matrix and achieve considerable performance gains. However, theoretically …