Determination of propagation model matrix in generalized cross-correlation based inverse model for broadband acoustic source localization

2020 ◽  
Vol 147 (4) ◽  
pp. 2098-2109
Author(s):  
Zhigang Chu ◽  
Jing Weng ◽  
Yang Yang
Keyword(s):  
Source Localization ◽  
Cross Correlation ◽  
Inverse Model ◽  
Propagation Model ◽  
Acoustic Source ◽  
Acoustic Source Localization ◽  
Model Matrix

Research on Acoustic Source Localization Technology Based on Cross-Correlation

2013 ◽  
Vol 819 ◽  
pp. 244-248
Author(s):  
Zhi Jiang Xie ◽  
Hai Zeng ◽  
Ping Chen
Keyword(s):  
Source Localization ◽  
Cross Correlation ◽  
Microphone Array ◽  
Noise Signal ◽  
Acoustic Source ◽  
Localization Accuracy ◽  
Correlation Algorithm ◽  
Acoustic Source Localization ◽  
Narrowband Signal ◽  
Improved Accuracy

In order to realize acoustic source localization, we proposed to use microphone array and time delay based on crosscorrelation algorithm,and analyzed the factors to influence the locating accuracy, and established a realtime acoustic source localizationsystem on the NI CompactRIO system. By experiments, cross-correlation algorithm for wideband signal(sweep signal, noise signal) localization is more accurate, for narrowband signal (organ signal) localization is less significant. After analyzed factors to influence the localization accuracy, we improved sound source system, and the factors that affected the organ signal localization is verified by experiment , and improved accuracy of narrowband signal localization .

scholarly journals Capabilities of inverse scheme for acoustic source localization at low frequencies

Acta Acustica ◽  
2021 ◽  
Vol 5 ◽  
pp. 44
Author(s):  
Stefan Gombots ◽  
Manfred Kaltenbacher ◽  
Barbara Kaltenbacher
Keyword(s):  
Source Localization ◽  
State Of The Art ◽  
Acoustic Source ◽  
Automatic Determination ◽  
Fe Method ◽  
Low Frequencies ◽  
Acoustic Environment ◽  
Acoustic Source Localization ◽  
Physical Boundary

We present the capabilities of a recently developed inverse scheme for source localization at low frequencies within an arbitrary acoustic environment. The inverse scheme is based on minimizing a Tikhonov functional matching measured microphone signals with simulated ones. We discuss the sensitivity of all involved parameters, the precision of geometry and physical boundary modeling for the numerical simulation using the finite element (FE) method, and the automatic determination of the positions of the recording microphones being distributed around the object of investigation. Finally, we apply the inverse scheme to a real-world scenario and compare the obtained results to state-of-the-art signal processing approaches, e.g. Clean-SC.

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