TY - JOUR
T1 - Acoustic Source Localization in a Reverberant Environment Based on Sound Field Morphological Component Analysis and Alternating Direction Method of Multipliers
AU - Chu, Ning
AU - Ning, Yue
AU - Yu, Liang
AU - Liu, Qin
AU - Huang, Qian
AU - Wu, Dazhuan
AU - Hou, Peng
N1 - Publisher Copyright:
© 1963-2012 IEEE.
PY - 2021
Y1 - 2021
N2 - The acoustic imaging results in the diffuse field are seriously affected by reverberation. The acoustic source localization algorithms based on the free-field assumption will produce many artifacts in the reverberant environment. To achieve accurate acoustic source localization in a reverberant environment, a sound field morphological component analysis (SF-MCA) model and an enhanced alternating direction method of multipliers (ADMM) algorithm are proposed in this article. First, the solution of the inhomogeneous Helmholtz equation is analyzed to characterize the acoustic components. Second, Green's function and plane-wave basis function serve as dictionaries for sparse representation of the acoustic signal in the frequency domain, and the corresponding decomposition coefficients are obtained by the enhanced ADMM algorithm. Finally, the accurate acoustic imaging results are realized in the reverberant chamber space with strong reverberation ( T20=174.30 ms ). Experiments demonstrate the validation of the proposed SF-MCA method. The acoustic imaging obtained by the proposed SF-MAC dereverberation model is far superior to the acoustic imaging that treats the reverberation as the general Gaussian noise.
AB - The acoustic imaging results in the diffuse field are seriously affected by reverberation. The acoustic source localization algorithms based on the free-field assumption will produce many artifacts in the reverberant environment. To achieve accurate acoustic source localization in a reverberant environment, a sound field morphological component analysis (SF-MCA) model and an enhanced alternating direction method of multipliers (ADMM) algorithm are proposed in this article. First, the solution of the inhomogeneous Helmholtz equation is analyzed to characterize the acoustic components. Second, Green's function and plane-wave basis function serve as dictionaries for sparse representation of the acoustic signal in the frequency domain, and the corresponding decomposition coefficients are obtained by the enhanced ADMM algorithm. Finally, the accurate acoustic imaging results are realized in the reverberant chamber space with strong reverberation ( T20=174.30 ms ). Experiments demonstrate the validation of the proposed SF-MCA method. The acoustic imaging obtained by the proposed SF-MAC dereverberation model is far superior to the acoustic imaging that treats the reverberation as the general Gaussian noise.
KW - Acoustic source localization
KW - alternating direction method of multipliers (ADMM)
KW - morphological component analysis (MCA)
KW - plane-wave basis function
KW - reverberant environment
KW - sparse decomposition
UR - http://www.scopus.com/inward/record.url?scp=85105555586&partnerID=8YFLogxK
U2 - 10.1109/TIM.2021.3077670
DO - 10.1109/TIM.2021.3077670
M3 - 文章
AN - SCOPUS:85105555586
SN - 0018-9456
VL - 70
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
M1 - 9423976
ER -