Covariance sparsity-aware DOA estimation for nonuniform noise
This paper reformulates the problem of direction-of-arrival (DOA) estimation for unknown
nonuniform noise by exploiting a sparse representation of the array covariance vectors. In …
nonuniform noise by exploiting a sparse representation of the array covariance vectors. In …
Off-grid DOA estimation using array covariance matrix and block-sparse Bayesian learning
Y Zhang, Z Ye, X Xu, N Hu - Signal Processing, 2014 - Elsevier
A new method based on a novel model for off-grid direction-of-arrival (DOA) estimation is
presented. The novel model is based on the sample covariance matrix and the off-grid …
presented. The novel model is based on the sample covariance matrix and the off-grid …
Drfm repeater jamming suppression method based on joint range-angle sparse recovery and beamforming for distributed array radar
B Han, X Qu, X Yang, Z Zhang, W Li - Remote Sensing, 2023 - mdpi.com
Distributed array radar achieves high angular resolution and measurement accuracy, which
could provide a solution to suppress digital radio frequency memory (DRFM) repeater …
could provide a solution to suppress digital radio frequency memory (DRFM) repeater …
DOA estimation based on sparse representation of the fractional lower order statistics in impulsive noise
This paper is mainly to deal with the problem of direction of arrival (DOA (estimations of
multiple narrow-band sources impinging on a uniform linear array under impulsive noise …
multiple narrow-band sources impinging on a uniform linear array under impulsive noise …
Sparse representation based direction-of-arrival estimation using circular acoustic vector sensor arrays
S Shi, Y Li, D Yang, A Liu, J Shi - Digital Signal Processing, 2020 - Elsevier
Abstract Direction-of-arrival (DOA) estimation using circular array has been attracted
significant attention in passive sonar system. Recently, the DOA estimation techniques face …
significant attention in passive sonar system. Recently, the DOA estimation techniques face …
Exploiting sparse recovery algorithms for semi-supervised training of deep neural networks for direction-of-arrival estimation
This paper proposes a semi-supervised training approach for a direction-of-arrival (DoA)
estimation based on a convolutional neural network (CNN). We apply a sparse recovery …
estimation based on a convolutional neural network (CNN). We apply a sparse recovery …
An improved near-field weighted subspace fitting algorithm based on niche particle swarm optimization for ultrasonic guided wave multi-damage localization
The ultrasonic guided wave-based method for multi-damage localization has been widely
proposed. However, the precision of this method is directly correlated with both the quantity …
proposed. However, the precision of this method is directly correlated with both the quantity …
DOA estimation of coherent signals based on the sparse representation for acoustic vector-sensor arrays
S Shi, Y Li, D Yang, A Liu, Z Zhu - Circuits, Systems, and Signal …, 2020 - Springer
This paper focuses on the problem of the DOA estimation of coherent signals for the acoustic
vector-sensor arrays (AVSAs) in the presence of the isotropic ambient noise. We propose a …
vector-sensor arrays (AVSAs) in the presence of the isotropic ambient noise. We propose a …
Robust sparse Bayesian learning for off-grid DOA estimation with non-uniform noise
The performance of traditional sparse representation-based direction-of-arrival (DOA)
estimation algorithm is substantially degraded in the presence of non-uniform noise and off …
estimation algorithm is substantially degraded in the presence of non-uniform noise and off …
Spatially smoothed TF-root-MUSIC for DOA estimation of coherent and non-stationary sources under noisy conditions
This paper proposes a method for efficient Direction-of-Arrival (DOA) estimation of coherent
and non-stationary sources under adverse noise conditions. The method consists of three …
and non-stationary sources under adverse noise conditions. The method consists of three …