Spherical t-Design for Characterizing the Spatial Response of Microphone Arrays

2021 ◽  
Author(s):  
Daniel Pinardi
Keyword(s):  
Microphone Arrays ◽  
Spatial Response

A Modified Chair Geometry for Whole Body Counting

1976 ◽  
Vol 15 (05) ◽  
pp. 246-247
Author(s):  
S. C. Jain ◽  
G. C. Bhola ◽  
A. Nagaratnam ◽  
M. M. Gupta
Keyword(s):  
Marked Improvement ◽  
Point Of View ◽  
Whole Body ◽  
Spatial Response ◽  
Body Counting ◽  
The Subject ◽  
Whole Body Counting ◽  
The Buddha

SummaryIn the Marinelli chair, a geometry widely used in whole body counting, the lower part of the leg is seen quite inefficiently by the detector. The present paper describes an attempt to modify the standard chair geometry to minimise this limitation. The subject sits crossed-legged in the “Buddha Posture” in the standard chair. Studies with humanoid phantoms and a volunteer sitting in the Buddha posture show that this modification brings marked improvement over the Marinelli chair both from the point of view of sensitivity and uniformity of spatial response.

scholarly journals Sound Localization for Ad-Hoc Microphone Arrays

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3446
Author(s):  
Muhammad Usman Liaquat ◽  
Hafiz Suliman Munawar ◽  
Amna Rahman ◽  
Zakria Qadir ◽  
Abbas Z. Kouzani ◽  
...  
Keyword(s):  
Sound Localization ◽  
Sound Source ◽  
Ad Hoc ◽  
Dimensional Space ◽  
Computation Time ◽  
Location Estimation ◽  
Microphone Arrays ◽  
Sound Signal ◽  
Experimental Arrangement ◽  
Advantages And Disadvantages

Sound localization is a field of signal processing that deals with identifying the origin of a detected sound signal. This involves determining the direction and distance of the source of the sound. Some useful applications of this phenomenon exists in speech enhancement, communication, radars and in the medical field as well. The experimental arrangement requires the use of microphone arrays which record the sound signal. Some methods involve using ad-hoc arrays of microphones because of their demonstrated advantages over other arrays. In this research project, the existing sound localization methods have been explored to analyze the advantages and disadvantages of each method. A novel sound localization routine has been formulated which uses both the direction of arrival (DOA) of the sound signal along with the location estimation in three-dimensional space to precisely locate a sound source. The experimental arrangement consists of four microphones and a single sound source. Previously, sound source has been localized using six or more microphones. The precision of sound localization has been demonstrated to increase with the use of more microphones. In this research, however, we minimized the use of microphones to reduce the complexity of the algorithm and the computation time as well. The method results in novelty in the field of sound source localization by using less resources and providing results that are at par with the more complex methods requiring more microphones and additional tools to locate the sound source. The average accuracy of the system is found to be 96.77% with an error factor of 3.8%.

scholarly journals Acoustic source localization using the open spherical microphone array in the low-frequency range

2019 ◽  
Vol 283 ◽  
pp. 04001
Author(s):  
Boquan Yang ◽  
Shengguo Shi ◽  
Desen Yang
Keyword(s):  
Source Localization ◽  
Generalized Inverse ◽  
Microphone Array ◽  
Low Frequency ◽  
Poor Performance ◽  
Microphone Arrays ◽  
Three Dimension ◽  
Frequency Range ◽  
Array Aperture ◽  
Regularization Matrix

Recently, spherical microphone arrays (SMA) have become increasingly significant for source localization and identification in three dimension due to its spherical symmetry. However, conventional Spherical Harmonic Beamforming (SHB) based on SMA has limitations, such as poor resolution and high side-lobe levels in image maps. To overcome these limitations, this paper employs the iterative generalized inverse beamforming algorithm with a virtual extrapolated open spherical microphone array. The sidelobes can be suppressed and the main-lobe can be narrowed by introducing the two iteration processes into the generalized inverse beamforming (GIB) algorithm. The instability caused by uncertainties in actual measurements, such as measurement noise and configuration problems in the process of GIB, can be minimized by iteratively redefining the form of regularization matrix and the corresponding GIB localization results. In addition, the poor performance of microphone arrays in the low-frequency range due to the array aperture can be improved by using a virtual extrapolated open spherical array (EA), which has a larger array aperture. The virtual array is obtained by a kind of data preprocessing method through the regularization matrix algorithm. Both results from simulations and experiments show the feasibility and accuracy of the method.

scholarly journals Minimax filters for microphone arrays

1999 ◽  
Vol 46 (12) ◽  
pp. 1522-1524 ◽  
Author(s):  
B.K. Lau ◽  
Y.H. Leung ◽  
K.L. Teo ◽  
V. Steeram
Keyword(s):  
Microphone Arrays
Sign in / Sign up

Export Citation Format

Share Document