arXiv · 1704.08953
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.
Explore related subjects
Keep this discovery
Hendrik Barfuss, Markus Bachmann, Michael Buerger, Martin Schneider, Walter Kellerman. 2017-04-28. Design of robust two-dimensional polynomial beamformers as a convex optimization problem with application to robot audition. https://arxiv.org/abs/1704.08953
Cite the original work for its findings. Save a collection to share your selection of sources.