Automatic estimation of position and orientation of an acoustic source by a microphone array network

2009 ◽  
Vol 126 (6) ◽  
pp. 3084-3094 ◽  
Author(s):  
Alberto Yoshihiro Nakano ◽  
Seiichi Nakagawa ◽  
Kazumasa Yamamoto
2013 ◽  
Vol 347-350 ◽  
pp. 922-926
Author(s):  
Ming Wang ◽  
Jian Hui Chen ◽  
Guang Long Wang ◽  
Feng Qi Gao ◽  
Ji Chen Li ◽  
...  

Acoustic source orientation is an important feature in robot audition. This paper applied a spatial cone six-element (SCSE) microphone array and combined with the time difference of arrival (TDOA) between pairs of spatial separated microphones to estimate acoustic source orientation. Simulate three stages of the acoustic orientation process in a real indoor environment, and results show that the algorithm is simple and effective, reducing the amount of calculation, having anti-noise and reverberation ability to meet the requirements of orientation accuracy.


2019 ◽  
Vol 146 (4) ◽  
pp. 3058-3059
Author(s):  
Mateusz Guzik ◽  
Konrad Kowalczyk ◽  
Szymon Woźniak ◽  
Mieszko Fraś ◽  
Klara Juros ◽  
...  

2017 ◽  
Vol 48 (3-4) ◽  
pp. 44-51 ◽  
Author(s):  
Gert Herold ◽  
Ennes Sarradj

The open-source Python library Acoular is aimed at the processing of microphone array data. It features a number of algorithms for acoustic source characterization in time domain and frequency domain. The modular, object-oriented architecture allows for flexible programming and a multitude of applications. This includes the processing of measured array data, the mapping of sources, the filtering of subcomponent noise, and the generation of synthetic data for test purposes. Several examples illustrating its versatility are given, as well as one example for implementing a new algorithm into the package.


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