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Predicting ocean pressure field with a physics-informed neural network
Ocean sound pressure field prediction, based on partially measured pressure magnitudes at
different range-depths, is presented. Our proposed machine learning strategy employs a …
different range-depths, is presented. Our proposed machine learning strategy employs a …
[HTML][HTML] 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 …
Passive source localization based on multipath arrival angles with a vertical line array using sparse Bayesian learning
In deep water, multipath time delays or frequency-domain interference periods of the
acoustic intensity combined with multipath arrival angles are typically used for source …
acoustic intensity combined with multipath arrival angles are typically used for source …
Bayesian optimization with Gaussian process surrogate model for source localization
Source localization with a geoacoustic model requires optimizing the model over a
parameter space of range and depth with the objective of matching a predicted sound field …
parameter space of range and depth with the objective of matching a predicted sound field …
[HTML][HTML] Gridless sparse covariance-based beamforming via alternating projections including co-prime arrays
This paper presents gridless sparse processing for direction-of-arrival (DOA) estimation. The
method solves a gridless version of sparse covariance-based estimation using alternating …
method solves a gridless version of sparse covariance-based estimation using alternating …
DOA M-estimation using sparse Bayesian learning
Recent investigations indicate that Sparse Bayesian Learning (SBL) is lacking in
robustness. We derive a robust and sparse Direction of Arrival (DOA) estimation framework …
robustness. We derive a robust and sparse Direction of Arrival (DOA) estimation framework …
[HTML][HTML] Graph-based sequential beamforming
This paper presents a Bayesian estimation method for sequential direction finding. The
proposed method estimates the number of directions of arrivals (DOAs) and their DOAs …
proposed method estimates the number of directions of arrivals (DOAs) and their DOAs …
Multi-source direction-of-arrival estimation using steered response power and group-sparse optimization
In this paper, a method is proposed for estimating the direction of arrival (DOA) of multiple
broadband sound sources. This is achieved by solving a group-sparse optimization …
broadband sound sources. This is achieved by solving a group-sparse optimization …
Direction finding method via acoustic vector sensor array with fluctuating misorientation
W Wang, X Li, Z Liu, W Shi, H Li - Applied Acoustics, 2023 - Elsevier
In this paper, we consider the direction-of-arrival (DOA) estimation problem under fluctuating
misorientation via acoustic vector sensor array (AVSA). A covariance matrix focusing fitting …
misorientation via acoustic vector sensor array (AVSA). A covariance matrix focusing fitting …
Newtonized orthogonal matching pursuit-based compressive spherical beamforming in spherical harmonic domain
S Yin, Y Yang, Z Chu, Y Yang - Mechanical Systems and Signal Processing, 2022 - Elsevier
Compressive spherical beamforming (CSB) with spherical microphone arrays is a promising
approach for acoustic source identification due to its high spatial resolution and applicability …
approach for acoustic source identification due to its high spatial resolution and applicability …