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 …

We propose an-norm constrained normalized least-mean-square (CNLMS) adaptive
beamforming algorithm for controllable sparse antenna arrays. To control the sparsity of the …

We introduce a novel image reconstruction method for time-resolved diffuse optical
tomography (DOT) that yields submillimeter resolution in less than a second. This opens the …

The problem of nonconvex and nonsmooth sparse representation for direction of arrival
(DOA) estimation in monostatic multiple-input multiple-output (MIMO) radar is addressed in …

It is studied that both the array mutual coupling (MC) and nonuniform noise could degrade
direction-of-arrival (DOA) estimators' performance substantially, and thus it is of necessity to …

Autonomous aerial vehicle (AAV)-assisted mobile edge computing systems have high
mobility and can be deployed in various rugged terrain and emergency scenarios for …

A deep‐learning‐based approach to estimating the number of coherent sources in radar is
presented. A proper estimate of the number of sources in a signal enables improved angle …

Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement
vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the …

The frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar is capable of
producing the angle-range-dependent beampattern by utilizing a small frequency increment …

The traditional parameter estimation method based on the matrix framework in multiple-input
multiple-output (MIMO) radar with sparse arrays loses the information of the tensor signal …