2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

Technical Program

Paper Detail

Paper IDAUD-15.4
Paper Title SPHERICAL HARMONIC REPRESENTATION FOR DYNAMIC SOUND-FIELD MEASUREMENTS
Authors Fabrice Katzberg, Marco Maass, Alfred Mertins, University of Lübeck, Germany
SessionAUD-15: Modeling, Analysis and Synthesis of Acoustic Environments 1: Soundfield Acquisition and Reproduction
LocationGather.Town
Session Time:Wednesday, 09 June, 16:30 - 17:15
Presentation Time:Wednesday, 09 June, 16:30 - 17:15
Presentation Poster
Topic Audio and Acoustic Signal Processing: [AUD-MAAE] Modeling, Analysis and Synthesis of Acoustic Environments
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Abstract Continuously moving microphones produce a high number of spatially dense sound-field samples with low effort in hardware and acquisition time. By interpreting the dynamic procedure as the non-uniform sampling of spatial basis functions, a system of linear equations can be set up. Its solution encodes sound-field parameters that allow for the spatio-temporal reconstruction within the measurement area at bandwidths where static methods would require impractical setups. An existing framework considers such basis functions from a signal processing point of view. It uses sinc-function based interpolation filters which are highly localized around sampled trajectories and may lead to ill-posed problems unless sparsity constraints are made, especially for locations that are away from microphone trajectories. In this paper, we present a new physical interpretation of the dynamic sampling problem. Transferring the problem into frequency domain, we describe samples of a moving microphone in terms of sampled spherical harmonic functions. The use of these global basis functions leads to dynamic measurements that inherently encode expanded sound-field information and, thus, allow for robust reconstruction at off-trajectory positions.