TY - GEN
T1 - MICROELECTROMECHANICAL SYSTEMS (MEMS) MICROPHONE ARRAY FOR SOUND SOURCE LOCALIZATION
AU - Wu, Chao Min
AU - Yao, Cheng Fu
N1 - Publisher Copyright:
© 2024 Proceedings of the International Congress on Sound and Vibration. All rights reserved.
PY - 2024
Y1 - 2024
N2 - 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 localization. The main purpose of this study is to compare the performance of four algorithms, Delay-And-Sum Beamforming (DAS), Minimum Power Distortionless Response Beamforming (MPDR), Multiple Signal Classification (MUSIC), and Clean-SC, in far-field sound source localization. By simulating the beam patterns of different array configurations between 200Hz and 6kHz, a well-performing spiral array configuration with 25 MEMS 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 time. The 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. Influenced 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. The results of simulation and experiment for a small array showed that Clean-SC can achieve higher accuracy, but more 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.
AB - 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 localization. The main purpose of this study is to compare the performance of four algorithms, Delay-And-Sum Beamforming (DAS), Minimum Power Distortionless Response Beamforming (MPDR), Multiple Signal Classification (MUSIC), and Clean-SC, in far-field sound source localization. By simulating the beam patterns of different array configurations between 200Hz and 6kHz, a well-performing spiral array configuration with 25 MEMS 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 time. The 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. Influenced 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. The results of simulation and experiment for a small array showed that Clean-SC can achieve higher accuracy, but more 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.
KW - Clean-SC
KW - Microphone Array
KW - Sound Field Visualization
KW - Source Localization
UR - http://www.scopus.com/inward/record.url?scp=85205394774&partnerID=8YFLogxK
M3 - 會議論文篇章
AN - SCOPUS:85205394774
T3 - Proceedings of the International Congress on Sound and Vibration
BT - Proceedings of the 30th International Congress on Sound and Vibration, ICSV 2024
A2 - van Keulen, Wim
A2 - Kok, Jim
PB - Society of Acoustics
T2 - 30th International Congress on Sound and Vibration, ICSV 2024
Y2 - 8 July 2024 through 11 July 2024
ER -