The scattering around the human pinna that is captured by the Head-Related Transfer Functions (HRTFs) is a complex problem that creates uncertainties in both acoustical measurements and simulations. Within the simulation framework of Finite Difference Time Domain (FDTD) with axis-aligned staircase boundaries resulting from a voxelization process, the voxelization-based uncertainty propagating in the HRTF-captured sound field is quantified for one solid and two surface voxelization algorithms. Simulated results utilizing a laser-scanned mesh of Knowles Electronics Manikin for Acoustic Research (KEMAR) show that in the context of complex geometries with local topology comparable to grid spacing such as the human pinna, the voxelization-related uncertainties in simulations emerge at lower frequencies than the generally used accuracy bandwidths. Numerical simulations show that the voxelization process induces both random error and algorithm-dependent bias in the simulated HRTF spectral features. Frequencies fr below which the random error is bounded by various dB thresholds are estimated and predicted. Particular shortcomings of the used voxelization algorithms are identified and the influence of the surface impedance on the induced errors is studied. Simulations are also validated against measurements.

Influence of voxelization on finite difference time domain simulations of head-related transfer functions

GERONAZZO, MICHELE;AVANZINI, FEDERICO;
2016

Abstract

The scattering around the human pinna that is captured by the Head-Related Transfer Functions (HRTFs) is a complex problem that creates uncertainties in both acoustical measurements and simulations. Within the simulation framework of Finite Difference Time Domain (FDTD) with axis-aligned staircase boundaries resulting from a voxelization process, the voxelization-based uncertainty propagating in the HRTF-captured sound field is quantified for one solid and two surface voxelization algorithms. Simulated results utilizing a laser-scanned mesh of Knowles Electronics Manikin for Acoustic Research (KEMAR) show that in the context of complex geometries with local topology comparable to grid spacing such as the human pinna, the voxelization-related uncertainties in simulations emerge at lower frequencies than the generally used accuracy bandwidths. Numerical simulations show that the voxelization process induces both random error and algorithm-dependent bias in the simulated HRTF spectral features. Frequencies fr below which the random error is bounded by various dB thresholds are estimated and predicted. Particular shortcomings of the used voxelization algorithms are identified and the influence of the surface impedance on the induced errors is studied. Simulations are also validated against measurements.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3192481
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