Augmented coarrays can be derived from spatially undersampled signals of sparse arrays
for underdetermined direction-of-arrival (DOA) estimation. With the extended dimension of …

Adaptive beamforming using sparse arrays can alleviate system burden with a sub-Nyquist
sampling rate while achieving high resolution. To process multi-dimensional signals without …

Adaptive beamforming plays an increasingly vital role in various applications, including
radar, sonar, telecommunications, and many other related fields. In this paper, we present …

Direction-of-arrival (DOA) estimation using sub-Nyquist tensor signals benefits from
enhanced performance by extracting structural angular information with multi-dimensional …

We consider signal source localization from range-difference measurements. First, we give
some readily-checked conditions on measurement noises and sensor deployment to …

Array sensor failure poses a serious challenge to robust direction-of-arrival (DOA) estimation
in complicated environments. Although existing matrix completion methods can successfully …

In this paper, we propose a novel deep learning (DL)-based gridless direction-of-arrival
(DOA) estimation method for generalized linear arrays using residual attention network …

Sparse direction-of-arrival (DOA) estimation methods can be formulated as a group-sparse
optimization problem. Meanwhile, sparse recovery methods based on noncovex penalty …

In recent years, nested conformal arrays have received considerable attention because they
are capable of providing extended array aperture and increased degrees of freedom …

To reduce the complexity of direction-of-arrival (DOA) algorithms in polarization-sensitive
arrays and maintain high estimation accuracy while decreasing runtime, this paper proposes …