Acoustic source localization with high performance sensor nodes

2007 ◽  
Author(s):  
M. R. Azimi-Sadjadi ◽  
G. Kiss ◽  
B. Fehér ◽  
S. Srinivasan ◽  
Á. Lédeczi
Keyword(s):  
Source Localization ◽  
High Performance ◽  
Sensor Nodes ◽  
Acoustic Source ◽  
Acoustic Source Localization

Acoustic Source Localization via Advanced TDoA for Self-Organization Wireless Sensor Networks

2011 ◽  
Vol 50-51 ◽  
pp. 42-48 ◽  
Author(s):  
Xuan Ya Li ◽  
Lin Lin Ci ◽  
Gen Yan Ge ◽  
Da Wei Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Source Localization ◽  
Physical World ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Self Organization ◽  
Acoustic Source ◽  
Acoustic Source Localization ◽  
Portable Sensor

Wireless Sensor Networks (WSNs) enable susceptible sensing of the environment, offering unprecedented opportunities for observing the physical world. Acoustic source localization is an interesting topic with many possible application areas, such as intruder detection, sniper localization, automatic tracking of speakers and so on. Many existing algorithms are on the premise that the exact coordinates of sensor nodes are already known. In this paper, we propose a vector-based advanced TDoA algorithm that would calibrate the coordinate of the acoustic source by the non-prepositioned nodes. In the meanwhile, the portable sensor nodes would adjust themselves through the feedback of the estimated positions as well. Finally, we show that the proposed mechanism has high accuracy through experiments.

scholarly journals Neural Networks for High Performance Time-Delay Estimation and Acoustic Source Localization

2017 ◽  
Author(s):  
Ludwig Houegnigan ◽  
Pooyan Safari ◽  
Climent Nadeu ◽  
Mike van der Schaar ◽  
Marta Sole ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Delay ◽  
Source Localization ◽  
High Performance ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Acoustic Source ◽  
Performance Time ◽  
Acoustic Source Localization

Square-shaped sensor clusters for acoustic source localization in anisotropic plates by wave front shape-based approach

2021 ◽  
Vol 153 ◽  
pp. 107489
Author(s):  
Novonil Sen ◽  
Mateusz Gawroński ◽  
Pawel Packo ◽  
Tadeusz Uhl ◽  
Tribikram Kundu
Keyword(s):  
Wave Front ◽  
Source Localization ◽  
Acoustic Source ◽  
Anisotropic Plates ◽  
Acoustic Source Localization ◽  
Front Shape

Utilizing laser distance sensors for audio recovery and acoustic source localization

2021 ◽  
Vol 149 (4) ◽  
pp. A43-A44
Author(s):  
Kanad Sarkar ◽  
Ryan M. Corey ◽  
Sri Vuppala ◽  
Andrew C. Singer
Keyword(s):  
Source Localization ◽  
Acoustic Source ◽  
Acoustic Source Localization

A fast approach for acoustic source localization on a thin spherical shell

2021 ◽  
pp. 147592172110419
Author(s):  
Zixian Zhou ◽  
Zhiwen Cui ◽  
Tribikram Kundu
Keyword(s):  
Velocity Profile ◽  
Spherical Shell ◽  
Source Localization ◽  
Pressure Vessels ◽  
Solution Technique ◽  
Acoustic Source ◽  
Spherical Shells ◽  
Fast Approach ◽  
Acoustic Source Localization ◽  
Thin Spherical Shell

Thin spherical shell structures are wildly used as pressure vessels in the industry because of their property of having equal in-plane normal stresses in all directions. Since very large pressure difference between the inside and outside of the wall exists, any formation of defects in the pressure vessel wall has a huge safety risk. Therefore, it is necessary to quickly locate the area where the defect maybe located in the early stage of defect formation and make repair on time. The conventional acoustic source localization techniques for spherical shells require either direction-dependent velocity profile knowledge or a large number of sensors to form an array. In this study, we propose a fast approach for acoustic source localization on thin isotropic and anisotropic spherical shells. A solution technique based on the time difference of arrival on a thin spherical shell without the prior knowledge of direction-dependent velocity profile is provided. With the help of “L”-shaped sensor clusters, only 6 sensors are required to quickly predict the acoustic source location for anisotropic spherical shells. For isotropic spherical shells, only 4 sensors are required. Simulation and experimental results show that this technique works well for both isotropic and anisotropic spherical shells.

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