Array measurements can be contaminated by strong noise, especially when dealing with microphones located near or in a flow. The denoising of these measurements is crucial to allow efficient data analysis or source imaging. In this paper, a denoising approach based on a Probabilistic Factor Analysis is proposed. It relies on a decomposition of the measured cross-spectral matrix (CSM) using the inherent correlation structure of the acoustical field and of the flow-induced noise. This method is compared with three existing approaches, aiming at denoising the CSM, without any reference or background noise measurements and without any information about the sources of interest. All these methods make the assumption that the noise is statistically uncorrelated over the microphones, and only one of them significantly impairs the off-diagonal terms of the CSM. The main features of each method are first reviewed, and the performances of the methods are then evaluated by way of numerical simulations along with measurements in a closed-section wind tunnel.
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May 04 2020
A probabilistic approach for cross-spectral matrix denoising: Benchmarking with some recent methods
Alice Dinsenmeyer
;
Alice Dinsenmeyer
a)
1
University of Lyon, INSA Lyon, Laboratoire Vibrations Acoustique
, F-69621 Villeurbanne, France
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Jérôme Antoni;
Jérôme Antoni
1
University of Lyon, INSA Lyon, Laboratoire Vibrations Acoustique
, F-69621 Villeurbanne, France
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Quentin Leclère;
Quentin Leclère
1
University of Lyon, INSA Lyon, Laboratoire Vibrations Acoustique
, F-69621 Villeurbanne, France
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Antonio Pereira
Antonio Pereira
2
University of Lyon, École Centrale de Lyon, INSA Lyon, Université Claude Bernard Lyon I, CNRS, Laboratoire de Mécanique des Fluides et d'Acoustique
, UMR 5509, F-69134 Écully, France
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a)
Also at: University of Lyon, École Centrale de Lyon, INSA Lyon, Université Claude Bernard Lyon I, CNRS, Laboratoire de Mécanique des Fluides et d'Acoustique, UMR 5509, F-69134 Écully, France. Electronic mail: alice.dinsenmeyer@insa-lyon.fr, ORCID: 0000-0002-6192-9206.
J. Acoust. Soc. Am. 147, 3108–3123 (2020)
Article history
Received:
December 13 2019
Accepted:
March 27 2020
Citation
Alice Dinsenmeyer, Jérôme Antoni, Quentin Leclère, Antonio Pereira; A probabilistic approach for cross-spectral matrix denoising: Benchmarking with some recent methods. J. Acoust. Soc. Am. 1 May 2020; 147 (5): 3108–3123. https://doi.org/10.1121/10.0001098
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