Design of robust two-dimensional polynomial beamformers as a convex optimization problem with application to robot audition

Barfuß H, Bachmann M, Bürger M, Schneider M, Kellermann W (2017)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2017

Pages Range: 106-110

Event location: New Paltz, NY US

ISBN: 978-1-5386-1631-4

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.

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How to cite

APA:

Barfuß, H., Bachmann, M., Bürger, M., Schneider, M., & Kellermann, W. (2017). Design of robust two-dimensional polynomial beamformers as a convex optimization problem with application to robot audition. In Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) (pp. 106-110). New Paltz, NY, US.

MLA:

Barfuß, Hendrik, et al. "Design of robust two-dimensional polynomial beamformers as a convex optimization problem with application to robot audition." Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), New Paltz, NY 2017. 106-110.

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