scholarly journals Fast Direction-of-Arrival Estimation for Single SourceNear- and Far-Field Approaches for 1D Source Localization

Author(s):  
Iurii Chyrka
2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 28413-28420
Author(s):  
Hojun Lee ◽  
Jongmin Ahn ◽  
Yongcheol Kim ◽  
Jaehak Chung

2021 ◽  
Vol 9 (09) ◽  
pp. 80-85
Author(s):  
Saulius Sakavicius ◽  

In this article theoretical analysis of the signal thresholding effects on the accuracy of cross-correlation based sound source direction of arrival estimation was presented. The aim of the investigation was to determine the theoretical limits and challenges of the accuracy of the localization of a speaker within an acoustic enclosure by cross-correlation of two microphone signals and to offer means to increase the accuracy of sound source direction of arrival estimation via selection of audio frames based on the time lag estimation realiability measure. For the investigation, audio material from an openly accessible database was used. Presented are the methods for obtaining various features of the microphone signal frames, signal amplitude to minimum error amplitude calculation and experimentation with threshold-based audio frame selection.


2020 ◽  
Vol 12 (0) ◽  
pp. 1-8
Author(s):  
Saulius Sakavičius

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.


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