Design of robust two-dimensional polynomial beamformers as a convex optimization problem with application to robot audition
Abstract
We propose a robust two-dimensional polynomial beamformer design method, formulated as a convex optimization problem, which allows for flexible steering of a previously proposed data-independent robust beamformer in both azimuth and elevation direction.~As an exemplary application, the proposed two-dimensional polynomial beamformer design is applied to a twelve-element microphone array, integrated into the head of a humanoid robot. To account for the effects of the robot's head on the sound field, measured head-related transfer functions are integrated into the optimization problem as steering vectors. The two-dimensional polynomial beamformer design is evaluated using signal-independent and signal-dependent measures. The results confirm that the proposed polynomial beamformer design approximates the original fixed beamformer design very accurately, which makes it an attractive approach for robust real-time data-independent beamforming.
Keywords
Cite
@article{arxiv.1704.08953,
title = {Design of robust two-dimensional polynomial beamformers as a convex optimization problem with application to robot audition},
author = {Hendrik Barfuss and Markus Bachmann and Michael Buerger and Martin Schneider and Walter Kellerman},
journal= {arXiv preprint arXiv:1704.08953},
year = {2017}
}
Comments
submitted to IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) 2017