[HTML][HTML] An off-grid direction-of-arrival estimator based on sparse Bayesian learning with three-stage hierarchical Laplace priors
N Li, XK Zhang, B Zong, F Lv, JH Xu, Z Wang - Signal Processing, 2024 - Elsevier
For direction-of-arrival (DOA) estimation problems, sparse Bayesian learning (SBL) has
achieved excellent estimation performance, especially in sparse arrays. However, numerous …
achieved excellent estimation performance, especially in sparse arrays. However, numerous …
Hybrid deconvolution method based on mode composition beamforming for separating sound sources with different motion modes
H Hou, F Ning, D Jia, W Li, J Wei - Journal of Sound and Vibration, 2024 - Elsevier
The presence of sound sources that rotate can cause interference with stationary acoustic
imaging, especially if the intensity of the rotating sound source is strong. Vice versa …
imaging, especially if the intensity of the rotating sound source is strong. Vice versa …
A novel sparse recovery‐based space‐time adaptive processing algorithm based on gridless sparse Bayesian learning for non‐sidelooking airborne radar
W Cui, T Wang, D Wang… - IET Radar, Sonar & …, 2023 - Wiley Online Library
Non‐sidelooking airborne radar encounters significant non‐stationary and heterogeneous
clutter environments, resulting in a severe shortage of samples. Sparse recovery‐based …
clutter environments, resulting in a severe shortage of samples. Sparse recovery‐based …
A Comprehensive Review of Direction-of-Arrival Estimation and Localization Approaches in Mixed-Field Sources Scenario
Direction-of-arrival (DOA) estimation plays a crucial role in array signal processing across
various domains, including radar, sonar, wireless communications, and seismic exploration …
various domains, including radar, sonar, wireless communications, and seismic exploration …
Super-Resolution Estimation of UWB Channels including the Diffuse Component--An SBL-Inspired Approach
In this paper, we present an iterative algorithm that detects and estimates the specular
components and estimates the diffuse component of single-input--multiple-output (SIMO) …
components and estimates the diffuse component of single-input--multiple-output (SIMO) …
Difference frequency gridless sparse array processing
Y Park, P Gerstoft - IEEE Open Journal of Signal Processing, 2024 - ieeexplore.ieee.org
This paper introduces a DOA estimation method for sources beyond the aliasing frequency.
The method utilizes multiple frequencies of sources to exploit the frequency difference …
The method utilizes multiple frequencies of sources to exploit the frequency difference …
Advanced Methods for MLE of Toeplitz Structured Covariance Matrices with Applications to RADAR Problems
This work considers Maximum Likelihood Estimation (MLE) of a Toeplitz structured
covariance matrix. In this regard, an equivalent reformulation of the MLE problem is …
covariance matrix. In this regard, an equivalent reformulation of the MLE problem is …
Robust and sparse m-estimation of doa
A robust and sparse Direction of Arrival (DOA) estimator is derived for array data that follows
a Complex Elliptically Symmetric (CES) distribution with zero-mean and finite second-order …
a Complex Elliptically Symmetric (CES) distribution with zero-mean and finite second-order …
Coarray LMS: Adaptive Underdetermined DOA Estimation with Increased Degrees of Freedom
Underdetermined direction of arrival (U-DOA) estimation refers to the ability to estimate the
DOA of more sources than the number of sensors in an array. Usually, to perform U-DOA …
DOA of more sources than the number of sensors in an array. Usually, to perform U-DOA …
Subspace representation learning for sparse linear arrays to localize more sources than sensors: A deep learning methodology
Localizing more sources than sensors with a sparse linear array (SLA) has long relied on
minimizing a distance between two covariance matrices and recent algorithms often utilize …
minimizing a distance between two covariance matrices and recent algorithms often utilize …