Assessing the performance of two new acoustic imaging techniques

Abstract

These are exciting times to work in the field of acoustics: researchers have a more granular understanding of sound than ever before due to the ability to acquire, store and analyze unprecedented amounts of acoustical data. The purpose of acoustic imaging is noise reduction. If noise can be measured, it can be reduced. Acoustic imaging is generally performed with a technique called conventional beamforming, which makes use of an array of microphones and of the phase of sound at the different microphones. Two new acoustic imaging techniques are Global Optimization and Source Power Integration, improving on the shortcomings of conventional beamforming. This thesis investigated the performance of Global Optimization and Source Power Integration in comparison to conventional beamforming. Two of the main findings are that the Global Optimization technique is good at precisely identifying closely spaced sound sources and that the Source Power Integration technique can accurately determine the sound power levels of distributed sources.