scholarly journals Sound field reconstruction using a spherical microphone array

2016 ◽  
Vol 139 (3) ◽  
pp. 1168-1178 ◽  
Author(s):  
Efren Fernandez-Grande
Keyword(s):  
Microphone Array ◽  
Sound Field ◽  
Field Reconstruction ◽  
Sound Field Reconstruction

Ghost Image Suppression Based on Particle Swarm Optimization-MVDR in Sound Field Reconstruction

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Min Li ◽  
Long Wei ◽  
Qiang Fu ◽  
Debin Yang
Keyword(s):  
Sound Source ◽  
Sound Pressure ◽  
Microphone Array ◽  
Sound Field ◽  
Distribution Map ◽  
Swarm Optimization ◽  
Field Reconstruction ◽  
Grating Lobe ◽  
Sound Field Reconstruction ◽  
Ghost Images

In sound field reconstruction, spurious sources called ghost images always appear around the position of the real sound source in the sound pressure distribution map because of the grating and side lobes, thus resulting in an incorrect identification of the sound source. To solve this problem, a method for suppressing ghost images is proposed in this paper; such method is based on particle swarm optimization (PSO) and minimum variance distortionless response (MVDR) beamforming. In this method, the elements distribution of a microphone array is first optimized by the PSO algorithm to acquire the optimal design of an unequal spacing microphone array. With this array, the grating lobe is suppressed, and the increscent value of the inherent side lobe value is reduced. Second, MVDR algorithm is used to weaken the effect of the side lobes and to obtain a sound pressure distribution map in which the ghost images are suppressed. The advantage of this method is the combination of the unequal spacing array, which suppresses the grating lobe, and the MVDR algorithm, which has excellent performance in spatial filtering. Through this method, a microphone array with a few number of elements can achieve ghost image suppression. Experiments on sound field reconstruction in an anechoic chamber for a single-tone sound source are conducted to validate the proposed method. Moreover, some extra sound field reconstructions for a single-tone sound source and double sound sources with broadband in a normal room with different parameters such as the array shape and distance from the sources to the array are conducted to discuss their influences on the effectiveness of the proposed method.

Gaussian processes for sound field reconstruction

2021 ◽  
Vol 149 (2) ◽  
pp. 1107-1119
Author(s):  
Diego Caviedes-Nozal ◽  
Nicolai A. B. Riis ◽  
Franz M. Heuchel ◽  
Jonas Brunskog ◽  
Peter Gerstoft ◽  
...  
Keyword(s):  
Gaussian Processes ◽  
Sound Field ◽  
Field Reconstruction ◽  
Sound Field Reconstruction

A sound field visualization system based on the wave superposition algorithm

2008 ◽  
Vol 222 (8) ◽  
pp. 1403-1412 ◽  
Author(s):  
J Q Li ◽  
J Chen ◽  
C Yang ◽  
G M Dong
Keyword(s):  
Numerical Simulations ◽  
Tikhonov Regularization ◽  
Sound Field ◽  
Point Sources ◽  
Experimental Results ◽  
Visualization System ◽  
Field Reconstruction ◽  
Wave Superposition ◽  
Sound Field Reconstruction ◽  
Regularization Strategy

Sound field visualization is a helpful design and analysis tool for the study of sound radiation and dispersion problems. It can help to comprehend deeply about noise transmission mechanism, monitor environment noise, evaluate sound quality, and even diagnose the machinery faults based on mechanical noise. The well-known near-field acoustic holography is an accurate sound field visualization technique. However, this technique has disadvantages such as strict measurement requirements and the need of an enormous number of microphones, which limits its extended applications. In order to visualize the sound field with a small number of microphones for measurements, the regeneration method of the radiated field by using the wave superposition algorithm is attempted in this study. It is based on the principle of equivalent source: the sound field radiated by an arbitrarily shaped radiator is substituted by the distributed point sources (monopole or dipole) constrained inside the actual source surface. For suppressing the adverse effect of measurement noise, the Tikhonov regularization strategy is adopted to work together with the wave superposition algorithm to give an accurate solution. Numerical simulations were performed based on a two-pulse-ball model to evaluate the accuracy of the combined algorithm of the wave superposition and the Tikhonov regularization strategy. In addition, an integrated sound field visualization system is designed and implemented. The functions include acoustic signal acquisition and processing, sound field reconstruction, and results visualization. The performance of the presented system was tested by experiments in a semi-anechoic chamber by using two sound boxes to simulate the sound sources. As concerning practical measurement microphones, there exist phase mismatches between the channels. Results will go wrong if the sound field reconstruction is performed directly with these uncalibrated measurement data. Therefore, a calibration procedure is applied to eliminate them. Experimental results indicate that the phase mismatches between the channels after calibration decay to 0.1°. Both the numerical simulations and experimental results accurately reconstructed the exterior sound field of the models. It is shown that the wave superposition algorithm together with the Tikhonov regularization strategy can exactly reconstruct the exterior sound field of radiators, which makes a base to its applications in practice. This sound field visualization system will make an operator's experimental work much easier.

Sign in / Sign up

Export Citation Format

Share Document