Spatial-fourier Retrieval of Head-related Impulse Responses from Fast Continuous-azimuth Recordings in the Time-domain

Abstract

Fast and comprehensive acquisition of head-related impulse responses (HRIRs) continues in the interest of rich application scenarios. Various HRIR resolutions have been presented based on discrete stop-and-go measurement, or comprehensive measurement equipment, or continuous-azimuth acquisition with moving apparatus. Some researchers have further mapped the recorded HRIR table to spatial Fourier format. In the interest of both fast acquisition and high accuracy, in this paper, we propose direct retrieval of the spatial Fourier format from time-domain recordings of the measurement signal. Specifically, we revert to the moving apparatus for HRIR measurement and express a generative model of the recorded signal based on a hypothetical spatial Fourier basis. In this approach, the spatial-Fourier model is meant to entirely capture the spatial variation of the HRIR. By least-squares inference we can then fit that model to the entire recording. Due to our time-domain treatment the model and the processing are entirely clean from block artifacts, while the huge dimension of the problem requires attention in the implementation. It turns out that the proposed algorithm significantly outperforms the previous NLMS-based continuous-azimuth acquisition of HRIR with moving apparatus.