An acoustic holography method with random sparse microphone array to locate moving sound sources

2008 ◽  
Author(s):  
Li Bing ◽  
Yang DianGe ◽  
Lian XiaoMin
Keyword(s):  
Microphone Array ◽  
Acoustic Holography ◽  
Sound Sources

Study of Spherical Near-Field Acoustic Holography with Rigid Spherical Microphone Array

2013 ◽  
Vol 546 ◽  
pp. 156-163
Author(s):  
Xin Guo Qiu ◽  
Ming Zong Li ◽  
Huan Cai Lu ◽  
Wei Jiang
Keyword(s):  
Sound Source ◽  
Microphone Array ◽  
Near Field ◽  
Sound Field ◽  
Acoustic Holography ◽  
Real Situation ◽  
Helmholtz Equations ◽  
Sound Sources ◽  
Array Configuration ◽  
Sphere Radius

The aim of this paper is to investigate the impacts of various parameters of rigid spherical microphone array in detecting and locating interior sound source. Helmholtz Equations are adopted to express the sound field produced by the incident field and scattered field. The gradient of the pressure is zero at the surface for the sphere is rigid. Both the incident and scattered coefficient could be obtained by solving the Helmholtz Equation using the boundary condition. Then the interior sound field could be detected and located on with the methodology of spherical near-field acoustic holography (SNAH). This study is developed in two aspects，one is configuring the microphone in various distribution in the same sphere radius, and the other one is changing the radius of sphere array. Numerical simulations are carried out to determine the optimum microphone array configuration and structure parameters. One, two, and three sound sources are arranged respectively in different displacement to the sphere center and in different angle direction to simulate the real situation. During the experiments, Omni-directional speakers and beeps are adopted as sound sources. The result shows that the method to detect and locate sound source in interior sound field is valid.

Locating and tracking sound sources on a horizontal axis wind turbine using a compact microphone array based on beamforming

2019 ◽  
Vol 146 ◽  
pp. 295-309 ◽  
Author(s):  
Cui Qing Zhang ◽  
Zhi Ying Gao ◽  
Yong Yan Chen ◽  
Yuan Jun Dai ◽  
Jian Wen Wang ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Microphone Array ◽  
Horizontal Axis ◽  
Horizontal Axis Wind Turbine ◽  
Sound Sources

Near Field Acoustic Holography for Cyclostationary Sound Field and its Partial Source Decomposition Procedure

2005 ◽  
Vol 127 (6) ◽  
pp. 542-546 ◽  
Author(s):  
Quan Wan ◽  
W. K. Jiang
Keyword(s):  
Principal Component Analysis ◽  
Sound Pressure ◽  
Near Field ◽  
Sound Field ◽  
Principal Component ◽  
Acoustic Holography ◽  
Sound Sources ◽  
Decomposition Procedure ◽  
Spectrum Density ◽  
Simulation Results

The cyclostationary near field acoustic holography (NAH) technique is proposed to overcome the limitations of the current NAH in analyzing cyclostationary sound field. The proposed technique adopts the cyclic spectrum density as the reconstructed physical quantity, instead of the spectrum of sound pressure. Moreover, introducing the principal component analysis into the technique, a partial source decomposition procedure is suggested to decompose the sound field radiated by multiple sound sources into some incoherent partial fields. More information about cyclostationary sound field can be shown clearly on the hologram of the proposed technique than NAH can, which is validated by the simulation results.

Layout Optimization of Cooperative Distributed Microphone Arrays Based on Estimation of Source Separation Performance

2017 ◽  
Vol 29 (1) ◽  
pp. 83-93
Author(s):  
Kouhei Sekiguchi ◽  
◽  
Yoshiaki Bando ◽  
Katsutoshi Itoyama ◽  
Kazuyoshi Yoshii
Keyword(s):  
Mobile Robots ◽  
Microphone Array ◽  
Source Separation ◽  
Microphone Arrays ◽  
Separation Performance ◽  
Sound Sources ◽  
Multiple Mobile Robots ◽  
Position Information ◽  
Reconfigurable Array ◽  
Source Signals

[abstFig src='/00290001/08.jpg' width='300' text='Optimizing robot positions for source separation' ] The active audition method presented here improves source separation performance by moving multiple mobile robots to optimal positions. One advantage of using multiple mobile robots that each has a microphone array is that each robot can work independently or as part of a big reconfigurable array. To determine optimal layout of the robots, we must be able to predict source separation performance from source position information because actual source signals are unknown and actual separation performance cannot be calculated. Our method thus simulates delay-and-sum beamforming from a possible layout to calculate gain theoretically, i.e., the expected ratio of a target sound source to other sound sources in the corresponding separated signal. Robots are moved into the layout with the highest average gain over target sources. Experimental results showed that our method improved the harmonic mean of signal-to-distortion ratios (SDRs) by 5.5 dB in simulation and by 3.5 dB in a real environment.

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