The University of Southampton
Engineering and the Environment

Research project: Next Generation Recording Technology

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Developing a microphone array with tangentially aligned pressure gradient sensors in combination with a novel spatial de-aliasing strategy.

Project Overview

Velocity microphone array
Velocity microphone array

 

Introduction

Over the past century, microphone arrays of different geometries have been the subject of acoustics research. Like many other types of sensor arrays, they simply serve the purpose of acquiring data of a sound field at a few discrete points. In combination with an adequate wave field model, the acquired data can be used to reconstruct the entire wave field both, physically and virtually. In other words, the sound field is known at any point in space that lies within the original model during the time of the recording.

The ability to reconstruct a wave field implicates that the data observed by the array carries sufficient information on the original wave field. Such an ambitious objective necessitates a sound mathematical model of the physics of any possible wave field under consideration and the sensor technology to keep the practical limitations of the model down to an acceptable level.

 

Tangential Pressure Gradient Sensor Array

What makes a sensor array design particularly interesting is the interpretation of the acquired data on the basis of an adequate wave field model. Ever since the first microphone array proposed by Alan Blumlein, the vast majority of designs rely on pressure sensors. Motivated by an initial study presented by Craven, Travis and Malcolm [1], we have been investigating the potential of arrays that apply pressure gradient sensors that are aligned tangentially to the arrayís measurement boundary.

 

A Post-Processing De-Aliasing Strategy

A microphone array and the sound field model it is based on should not only be judged by its baseline performance but also by the potential it bears for further signal processing to be applied. A carefully designed post-processing of the acquired sound field data can further improve the performance of the overall system.

We are working on a signal processing strategy that seeks to tackle spatial aliasing in circular microphones. Using a sound field model with a finite number of plane waves, the data recovered from the optimum frequency band of an existing microphone array can be used to identify these ëprincipalí plane waves. Assuming that the sources in the sound field are radiating over a wide frequency band, it can be assumed that the wave field at higher frequencies (which are typically affected by aliasing) originates from the same sources and can therefore be represented by the same principal plane waves. Using an aliasing model for single plane waves, the spatial aliasing occurring at higher frequencies can be accounted for and successfully removed from the observed data.

 

Falk-Martin Hoffman, Filippo Fazi

 

 

[1] P. G. Craven, M. J. Law, and C. Travis, ìMicrophone arrays using tangential velocity sensors,î in Ambisonics Symposium, June 2009.

 

 

Related research groups

Acoustics Group

Staff

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