estimate_early_reflections_OMP.ipynb creates the figures
of
Frank Schultz, Sascha Spors (2019): "On the detection quality of early room reflection directions using compressive sensing on rigid spherical microphone array data", In: Proc. of 23rd Intl Congress on Acoustics, Aachen, Germany, 2676-2683.
Here, we compare direction of arrival (DOA) of early room reflections using plane wave decomposition (PWD, top figure) vs. compressive sensing (CS) using orthogonal matching pursuit (OMP, bottom figure) for a certain room scenario and different microphone array configurations.
Figure 2 from paper: Early room reflections’ DOA over time. Left: azimuth, right: colatitude, top: PWD |pφm×θm×t| in dB, bottom: CS-OMP |xφm×θm×t| in dB. Rigid microphone array, spherical Lebedev grid with 170 receivers, 4th order image source model, all walls brick (absorption coefficient 0.15), no additive noise.
The paper can be found here in the repository. The poster can be found here in the repository.
The conda environmet conda_environment.yml might be required to run the code
properly, there are some dependencies of older packages involved.
Furthermore, we require
https://github.com/sfstoolbox/sfs-python (commit 3453e987ee742bd1c4af42af0c405df8363e6a4d worked)
https://github.com/spatialaudio/sfa-numpy (commit bff5737ef429f31228d20a9e1d0ce7d46d3080d3 worked)
for image source modelling and sound field analysis stuff.