In this article, we study the radar angular resolution, the capability of distinguishing multiple
targets in different directions of arrivals (DoA). We present a deep learning-based super …

In this work, we propose an alternating low-rank decomposition (ALRD) approach and novel
subspace algorithms for direction-of-arrival (DOA) estimation. In the ALRD scheme, the …

The issue of asset tracking in dense environments where the performance of the global
positioning system (GPS) becomes unavailable or unreliable is addressed. The proposed …

In this paper, a reduced-rank scheme with joint iterative optimization is presented for
direction of arrival estimation. A rank-reduction matrix and an auxiliary reduced-rank …

In this work, we propose a subspace-based algorithm for direction-of-arrival (DOA)
estimation that iteratively reduces the disturbance factors of the estimated data covariance …

Several algorithms for direction-of-arrival (DOA) estimation with uniform circular arrays rely
on the beamspace transform as it allows computationally efficient estimation of the angles-of …

In this paper, we explore the problem of direction-of-arrival (DOA) estimation for a non-
uniform linear array (NULA) under strong noise. The compressed sensing (CS)-based …

In this paper, we consider the problem of low dimensional signal subspace estimation in a
Bayesian context. We focus on compound Gaussian signals embedded in white Gaussian …

In the light of recent developments in optimal real L 1-norm principal-component analysis
(PCA), we provide the first algorithm in the literature to carry out L 1-PCA of complex-valued …

This paper proposes a new algorithm for the direction of arrival (DOA) estimation of P
radiating sources. Unlike the classical subspace-based methods, it does not resort to the …