scholarly journals A model-based Bayesian framework for sound source enumeration and direction of arrival estimation using a coprime microphone array

2018 ◽  
Vol 143 (6) ◽  
pp. 3934-3945 ◽  
Author(s):  
Dane Bush ◽  
Ning Xiang
Keyword(s):  
Sound Source ◽  
Microphone Array ◽  
Direction Of Arrival ◽  
Bayesian Framework ◽  
Direction Of Arrival Estimation ◽  
Model Based

scholarly journals DATASET FOR EVALUATION OF THE PERFORMANCE OF THE METHODS OF SOUND SOURCE LOCALIZATION ALGORITHMS USING TETRAHEDRAL MICROPHONE ARRAYS

2020 ◽  
Vol 12 (0) ◽  
pp. 1-8
Author(s):  
Saulius Sakavičius
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Microphone Array ◽  
Direction Of Arrival ◽  
Microphone Arrays ◽  
Sound Source Localization ◽  
Direction Of Arrival Estimation ◽  
Sound Sources ◽  
Localization Algorithms ◽  
Geometrical Information

For the development and evaluation of a sound source localization and separation methods, a concise audio dataset with complete geometrical information about the room, the positions of the sound sources, and the array of microphones is needed. Computer simulation of such audio and geometrical data often relies on simplifications and are sufficiently accurate only for a specific set of conditions. It is generally desired to evaluate algorithms on real-world data. For a three-dimensional sound source localization or direction of arrival estimation, a non-coplanar microphone array is needed.Simplest and most general type of non-coplanar array is a tetrahedral array. There is a lack of openly accessible realworld audio datasets obtained using such arrays. We present an audio dataset for the evaluation of sound source localization algorithms, which involve tetrahedral microphone arrays. The dataset is complete with the geometrical information of the room, the positions of the sound sources and the microphone array. Array audio data was captured for two tetrahedral microphone arrays with different distances between microphones and one or two active sound sources. The dataset is suitable for speech recognition and direction-of-arrival estimation, as the signals used for sound sources were speech signals.

scholarly journals AR Model-Based Direction-of-Arrival Estimation of Coherent Signals in the Presence of Unknown Mutual Coupling

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Zhi-Chao Sha ◽  
Zhang-Meng Liu ◽  
Zhi-Tao Huang ◽  
Yi-Yu Zhou
Keyword(s):  
Mutual Coupling ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Ar Model ◽  
Estimation Accuracy ◽  
Direction Of Arrival Estimation ◽  
Coherent Signals ◽  
Model Based ◽  
Mixing Matrix ◽  
Simulation Results

This paper addresses the problem of direction-of-arrival (DOA) estimation of coherent signals in the presence of unknown mutual coupling, and an autoregression (AR) model-based method is proposed. The effects of mutual coupling can be eliminated by the inherent mechanism of the proposed algorithm, so the DOAs can be accurately estimated without any calibration sources. After the mixing matrix is estimated by independent component analysis (ICA), several parameter equations are established upon the mixing matrix. Finally, all DOAs of coherent signals are estimated by solving these equations. Compared with traditional methods, the proposed method has higher angle resolution and estimation accuracy. Simulation results demonstrate the effectiveness of the algorithm.

Model-based direction of arrival estimations for sound sources using a spherical microphone array

2018 ◽  
Vol 144 (3) ◽  
pp. 1882-1882
Author(s):  
Christopher R. Landschoot ◽  
Jonathan Mathews ◽  
Jonas Braasch ◽  
Ning Xiang
Keyword(s):  
Microphone Array ◽  
Direction Of Arrival ◽  
Sound Sources ◽  
Model Based
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