Two-dimensional (2D) arrays are fundamental to localization applications. Specifically,
sparse arrays can provide superior direction-of-arrival (DoA) estimation performance with …

Coprime arrays can achieve an increased number of degrees of freedom by deriving the
equivalent signals of a virtual array. However, most existing methods fail to utilize all …

The Cramér-Rao Bound (CRB) for direction of arrival (DOA) estimation has been extensively
studied over the past four decades, with a plethora of CRB expressions reported for various …

Recently, many sparse-based methods have been proposed for direction-of-arrival (DOA)
estimation. However, these methods often suffer from the grid mismatch problem caused by …

A coprime array is capable of achieving more degrees-of-freedom for direction-of-arrival
(DOA) estimation than a uniform linear array when utilizing the same number of sensors …

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 …

Unknown mutual coupling effect can degrade the performance of a direction of arrival
estimation method. In this letter, a new method is proposed for uniform linear arrays (ULAs) …

In this paper, a novel localization method for mixed near-field (NF) and far-field (FF)
rectilinear or strictly noncircular sources is proposed using the noncircular information for a …

Widely linear (WL) robust adaptive beamforming exhibits superior performance by effectively
leveraging the additional noncircularity information. However, existing studies focus solely …

In this letter, we devise a cylindrical conformal array with nested subarray structures and
propose a two-dimensional (2-D) direction-of-arrival (DOA) algorithm via sparse …