Tampere University of Technology

TUTCRIS Research Portal

Local Time-Domain Spherical Harmonic Spatial Encoding for Wave-Based Acoustic Simulation

Research output: Contribution to journalArticleScientificpeer-review

Standard

Local Time-Domain Spherical Harmonic Spatial Encoding for Wave-Based Acoustic Simulation. / Bilbao, Stefan; Politis, Archontis; Hamilton, Brian.

In: IEEE Signal Processing Letters, Vol. 26, No. 4, 01.04.2019, p. 617-621.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Bilbao, S, Politis, A & Hamilton, B 2019, 'Local Time-Domain Spherical Harmonic Spatial Encoding for Wave-Based Acoustic Simulation', IEEE Signal Processing Letters, vol. 26, no. 4, pp. 617-621. https://doi.org/10.1109/LSP.2019.2902509

APA

Vancouver

Author

Bilbao, Stefan ; Politis, Archontis ; Hamilton, Brian. / Local Time-Domain Spherical Harmonic Spatial Encoding for Wave-Based Acoustic Simulation. In: IEEE Signal Processing Letters. 2019 ; Vol. 26, No. 4. pp. 617-621.

Bibtex - Download

@article{a743f1f6a59a4a089f74833ebec55a0c,
title = "Local Time-Domain Spherical Harmonic Spatial Encoding for Wave-Based Acoustic Simulation",
abstract = "Volumetric time-domain simulation methods, such as the finite difference time domain method, allow for a fine-grained representation of the dynamics of the acoustic field. A key feature of such methods is complete access to the computed field, normally represented over a Cartesian grid. Simple solutions to the problem of extracting spatially encoded signals, necessary in virtual acoustics applications, result. In this letter, a simple time-domain representation of spatially encoded spherical harmonic signals is written directly in terms of spatial derivatives of the acoustic field at the receiver location. In a discrete setting, encoded signals may be obtained, at very low computational cost and latency, using local approximations with minimal number of grid points, and avoiding large convolutions and frequency-domain block processing of previous approaches. Numerical results illustrating receiver directivity and computed time-domain responses are presented, as well as numerical solution drift associated with repeated time integration.",
keywords = "acoustic field, acoustic signal detection, acoustic signal processing, encoding, finite difference time-domain analysis, frequency-domain analysis, time-domain analysis, repeated time integration, computed time-domain responses, frequency-domain block processing, spatially encoded spherical harmonic signals, simple time-domain representation, virtual acoustics applications, spatially encoded signals, computed field, fine-grained representation, finite difference time domain method, volumetric time-domain simulation methods, wave-based acoustic simulation, local time-domain spherical harmonic spatial encoding, Time-domain analysis, Acoustics, Encoding, Harmonic analysis, Finite difference methods, Three-dimensional displays, Receivers, Finite difference time domain (FDTD), room acoustics, spatial audio, microphone array, spherical harmonics, ambisonics",
author = "Stefan Bilbao and Archontis Politis and Brian Hamilton",
year = "2019",
month = "4",
day = "1",
doi = "10.1109/LSP.2019.2902509",
language = "English",
volume = "26",
pages = "617--621",
journal = "IEEE Signal Processing Letters",
issn = "1070-9908",
publisher = "Institute of Electrical and Electronics Engineers",
number = "4",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Local Time-Domain Spherical Harmonic Spatial Encoding for Wave-Based Acoustic Simulation

AU - Bilbao, Stefan

AU - Politis, Archontis

AU - Hamilton, Brian

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Volumetric time-domain simulation methods, such as the finite difference time domain method, allow for a fine-grained representation of the dynamics of the acoustic field. A key feature of such methods is complete access to the computed field, normally represented over a Cartesian grid. Simple solutions to the problem of extracting spatially encoded signals, necessary in virtual acoustics applications, result. In this letter, a simple time-domain representation of spatially encoded spherical harmonic signals is written directly in terms of spatial derivatives of the acoustic field at the receiver location. In a discrete setting, encoded signals may be obtained, at very low computational cost and latency, using local approximations with minimal number of grid points, and avoiding large convolutions and frequency-domain block processing of previous approaches. Numerical results illustrating receiver directivity and computed time-domain responses are presented, as well as numerical solution drift associated with repeated time integration.

AB - Volumetric time-domain simulation methods, such as the finite difference time domain method, allow for a fine-grained representation of the dynamics of the acoustic field. A key feature of such methods is complete access to the computed field, normally represented over a Cartesian grid. Simple solutions to the problem of extracting spatially encoded signals, necessary in virtual acoustics applications, result. In this letter, a simple time-domain representation of spatially encoded spherical harmonic signals is written directly in terms of spatial derivatives of the acoustic field at the receiver location. In a discrete setting, encoded signals may be obtained, at very low computational cost and latency, using local approximations with minimal number of grid points, and avoiding large convolutions and frequency-domain block processing of previous approaches. Numerical results illustrating receiver directivity and computed time-domain responses are presented, as well as numerical solution drift associated with repeated time integration.

KW - acoustic field

KW - acoustic signal detection

KW - acoustic signal processing

KW - encoding

KW - finite difference time-domain analysis

KW - frequency-domain analysis

KW - time-domain analysis

KW - repeated time integration

KW - computed time-domain responses

KW - frequency-domain block processing

KW - spatially encoded spherical harmonic signals

KW - simple time-domain representation

KW - virtual acoustics applications

KW - spatially encoded signals

KW - computed field

KW - fine-grained representation

KW - finite difference time domain method

KW - volumetric time-domain simulation methods

KW - wave-based acoustic simulation

KW - local time-domain spherical harmonic spatial encoding

KW - Time-domain analysis

KW - Acoustics

KW - Encoding

KW - Harmonic analysis

KW - Finite difference methods

KW - Three-dimensional displays

KW - Receivers

KW - Finite difference time domain (FDTD)

KW - room acoustics

KW - spatial audio

KW - microphone array

KW - spherical harmonics

KW - ambisonics

U2 - 10.1109/LSP.2019.2902509

DO - 10.1109/LSP.2019.2902509

M3 - Article

VL - 26

SP - 617

EP - 621

JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

SN - 1070-9908

IS - 4

ER -