Entwicklung und Evaluierung von Algorithmen zur Schallquellenlokalisation mit koinzidenten Mikrofonarrays

The Diploma thesis is locked.

A typical application of microphone arrays is to estimate the position of sound sources. The term microphone array is usually related to an arrangement of several microphones placed at different locations. Within this thesis, however, acoustic source localisation (ASL) using coincident - and thus inherently space-saving and handy - microphone arrays will be tackled.

Besides an established method based on analysing the direction of the intensity vector, a pattern recognition approach for ASL is presented. A minimum distance classifier is employed, i.e. feature vectors calculated frame by frame from the array signals are compared with a pre-recorded feature-database. The characteristics of the presented approaches are discussed with the help of a mathematical model of first order gradient microphones, as well as with measurements with a planar 4-channel coincident array prototype.

Particular focus is given to robust speaker-tracking in noisy environments. In this context, several advances to the basic algorithm for improving robustness and accuracy are proposed. All the algorithms are implemented in a single, easy to use, MATLAB function. In addition to source localisation, a brief outline of beamforming using coincident arrays is given.

The performance of the presented ASL-algorithms is evaluated using array recordings of static and moving sound sources. Different signal to noise ratios are considered. As a basis for quantification of the estimation error, the actual position of the sound source was measured with an optical tracking system. The obtained azimuth estimation results are very promising and show the practicability of the presented approach.