Reconstruction of room impulse responses over an extended spatial domain using block-sparse and kernel regression methods

The acquisition of the spatio-temporal properties of a sound field over large spatial domains is a challenging task that requires a large number of transducers. Alternatively to these classical approaches, sound field reconstruction methods utilise fewer measurements and enable the interpolation and extrapolation of the measured data. This study exploits the spatio-temporal characteristics of the room impulse response (RIR) to reconstruct the sound field over large spatial apertures. The direct sound field and the early reflections are reconstructed using block-sparsity techniques, and therefore no assumption is made upon the wavefronts. Finally, the late reverberation of the RIR is evaluated using kernel ridge regression, taking advantage of the generalisable stochastic properties of random wave fields. The proposed model reconstructs accurately the RIRs and outperforms classical approaches that are based on the use of plane waves, which are used here as a benchmark for comparison.