Fundamentals of a Parametric Method for Virtual Navigation Within an Array of Ambisonics Microphones

Abstract

Fundamental aspects of a method for virtual navigation of a sound field within an array of ambisonics microphones, wherein the subset of microphones to be used for interpolation is determined parametrically, are presented. An existing, weighted-average-based navigational method serves as a benchmark due to its simplicity and its applicability to arbitrary sound fields but introduces comb-filtering and, for near-field sources, degrades localization. A critical review of existing methods is presented, through which a number of issues are identified. In the proposed method, those microphones that are nearer to the desired listening position than to any source are determined based on the known or inferred positions of sources. The signals from only those microphones are then interpolated using a regularized least-squares matrix of filters. Spectral distortions and source localization errors are characterized for the benchmark and proposed methods via numerical simulations of a two-microphone array, and an experimental validation of these simulations is presented. Results show that, for near-field sources, the proposed method significantly outperforms the benchmark in both spectral and localization accuracy due to the exclusion of the second microphone. For far-field sources, the proposed method achieves slightly decreased spectral distortions due to the flattened response of the interpolation filters.

Locating Image Sources from Multiple Spatial Room Impulse Responses

“…In fact, Müller and Zotter [25] have recently presented a measurement-based rendering system that works on first order Ambisonics impulse responses. Additionally, there are several other methods for rendering continuous sound signals in 6DoF [26][27][28][29][30][31][32][33] that could be potentially adapted to process impulse responses as well. However, the latter methods would not specifically focus on the correctness of early reflections.…”

Immersive audio, capture, transport, and rendering: a review

“…Equation (12) shows the reconstruction error is a function of kr, where p(kr, θ , ϕ) represents the original soundfield, and p M (kr, θ , ϕ) is the soundfield truncated up to order M in practice. This function represents the distance to the center of the array and is frequency-dependent.…”

“…Recent years have seen some popularity of distributed recording of soundfield using multiple FOA or HOA microphones [10][11][12]. As evident in previous discussion, coincident FOA microphones only offer limited spatial resolution and the perceived spaciousness and the size of the sweet spot in loudspeaker reproduction are also limited due to the high level of interchannel correlation.…”

“…Recent years have seen some popularity of distributed recording of soundfield using multiple FOA or HOA microphones [10–12].…”

Performance of Linear Extrapolation Methods for Virtual Sound Field Navigation

“…Several other authors have developed linear and parametric interpolation-based navigational methods [30-34, and references therein], which employ an array of HOA microphones and are expected to yield significant improvements compared to extrapolation methods in terms of spectral coloration and source localization. While it is outside the scope of this work to discuss these methods in detail, a critical review of such methods is given by Tylka and Choueiri [35].…”