| dc.description.abstract | Sound source localization is a difficult problem in engineering. Traditional methods generally cannot locate sound sources effectively. Due to the development of technology in hardware and signal processing, the microphone array can be used for source identification.
Recently the application of sound source localization has grown rapidly, and many algorithms have been developed for it. Three common techniques are Delay-And-Sum Beamforming (DAS), Minimum Power Distortionless Response Beamforming (MPDR), and Multiple Signal Classification (MUSIC). As computing power grows exponentially, deconvolution algorithms, such as Clean-SC, have been developed. This study compares the performance of four algorithms, such as DAS, MPDR, MUSIC and, Clean-SC, in far-field sound source localization.
A small-sized microphone array was used in this study. By simulating the beam patterns of different array configurations between 200Hz and 6kHz, a well-performing spiral array configuration with 25 microphones was chosen. The simulation of single source showed that DAS and MPDR took less computational time but reduced the accuracy; MUSIC and Clean-SC were more accurate at the expense of computing. Much more computing time were required for Clean-SC than for MUSIC. Two source simulation considered three distance, 55cm, 35cm ,and 15cm, between two sources. In 55cm simulation, DAS and Clean-SC could not locate two sources at 2000Hz. Four algorithms were able to distinguish two sources at 3000Hz and 4000Hz. Because, DAS could not locate two sources 35cm and 15cm apart. 55cm was chosen for the distance between the two sources in the experiment.
The experiment was carried out in a reverberant room. At 2000Hz, the results revealed that four algorithms were able to find the position of a sound source locating at the tweeters of the speaker. Due to the overlapping of the main lobes, MPDR could not distinguish two sound sources. MUSIC was able to locate two sources but slightly deviated 8cm. Influencing by DAS, Clean-SC located the sound source incorrectly. At 3000Hz, only MUSIC was able to locate two sources but with lower accuracy. However, for 4000Hz, four algorithms could not locate two sources.
Finally, the results of simulation and experiment of a small array showed that Clean-SC, based on deconvolution, can achieve higher accuracy, but exchanged for computational time, compared to DAS, MPDR, and MUSIC in single source localization. MUSIC has better performance for multiple sound sources in reverberant environments. The narrow-band algorithm is used in this research. In the future, it is hoped to apply Coherent Subspace Method to detect sound sources with different frequencies. | en_US |