The Ray Space Transform: A New Framework for Wave Field Processing

Abstract

Soundfield imaging is a special analysis methodology aimed at capturing the directional components of the acoustic field and mapping them onto a domain called "ray space", where rele-vant acoustic objects become linear patterns, i.e., sets of collinear points. This allows us to overcome resolution issues while easing far-field assumptions. In this paper, we generalize this concept by introducing the ray space transform for acoustic field repre-sentation. The transform is based on a short space-time Fourier transform of the signals captured by a microphone array, using discrete Gabor frames. The resulting transform coefficients are parameterized in the same ray space used for soundfield imaging. The resulting transform enables the definition of analysis and syn-thesis operators, which exhibit perfect reconstruction capabilities. We show examples of applications of the ray space transform to source localization and spot spatial filtering.

A Methodology for Sound Scene Manipulation Based on the Ray Space Transform

“…In this section we define the data model adopted in this manuscript and review the Ray Space Transform (RST) introduced in [7] that will be applied to the array signal.…”

“…The localization is performed upon considering the wideband extension Y ∈ R I×W of the RST, computed as the geometric mean along the K/2 frequency bins of the absolute value of the coefficients matrix |Y(ω k )| [7]. From Y one peak is identified for each i-th row at valuesm i and amplitude λ i .…”

Extraction of acoustic sources for multiple arrays based on the ray space transform

“…In [13], the ray space parameterization is adopted, in which a plane wave component is represented by an acoustic ray, i.e. the direction locally orthogonal to the plane wave.…”

“…As done in [13], we transform the integral equation in (1), which can be repurposed for the ath discrete array (a = 1, . .…”

“…In this paper we propose a filter design technique for this scenario. More precisely, we adopt the Ray Space Transform representation of the sound field recently introduced in [13]. The advantage of the Ray Space Transform is that it provides analysis and synthesis operators, which exhibit perfect reconstruction capabilities, thus making it possible to perform processing operations in the Ray Space in a lossless fashion, while keeping the geometrical intuitive representation of the Ray Space [14].…”