Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.698362
Title: Signal processing for microphone arrays with novel geometrical design
Author: Tontiwattanakul, Khemapat
ISNI:       0000 0004 5990 6325
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2016
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Abstract:
This research aims to propose a novel technique to design rigid baffle microphone arrays with complex geometry and their signal processing. The proposed technique relies on the use of the boundary element method (BEM) that allows to obtain a numerical model of the acoustic pressure captured by sensors of microphone arrays with any geometry. The beamforming strategy proposed in this study is based on the singular value decomposition (SVD), which is regarded as the general idea of the modal beamforming. In this research, the microphone array problem is setup in an inverse problem framework,and is formulated as a Fredholm's integral equation of the first kind. The beamformer is then realised and the discrete version of the problem is analysed and discussed. The proposed design technique is then applied to two case studies: ?firstly, to study spheroidal microphone array and, secondly, to study spherical microphone arrays with acoustic waveguides added to the surface of the arrays with the aim to extend their operating frequency bandwidth. Number of numerical simulations were carried out in both studies. The most significant results are presented in the second case study. It is proved via numerical simulations that the cavities on the spherical array allow for the reduction of spatial aliasing error. Moreover, the relation between the spherical harmonic beamforming and the SVD beamformer is discussed. An experiment was setup in order to demonstrate that the array with waveguides achieves the desired e?ffect with realisable. The experiment results indicate that the proposed technique is practical and can be implemented for real-life microphone array design.
Supervisor: Fazi, Filippo Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.698362  DOI: Not available
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