Design of robust superdirective beamformers as a convex optimization problem

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Mabande E, Schad A, Kellermann W
Publication year: 2009
Pages range: 77-80
ISBN: 978-1-4244-2353-8
ISSN: 1520-6149
Language: English


Abstract


Broadband data-independent beamforming designs aiming at constant beamwidth often lead to superdirective beamformers for low frequencies, if the sensor spacing is small relative to the wavelengths. Superdirective beamformers are extremely sensitive to spatially white noise and to small errors in the array characteristics. These errors are nearly uncorrelated from sensor to sensor and affect the beamformer in a manner similar to spatially white noise. Hence the White Noise Gain (WNG) is a commonly used measure for the robustness of beamformer designs. In this paper, we present a method which incorporates a constraint for the WNG into a least-squares beamformer design and still leads to a convex optimization problem that can be solved directly, e.g. by Sequential Quadratic Programming. The effectiveness of this method is demonstrated by design examples. ©2009 IEEE.


FAU Authors / FAU Editors

Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik
Mabande, Edwin
Professur für Nachrichtentechnik


How to cite

APA:
Mabande, E., Schad, A., & Kellermann, W. (2009). Design of robust superdirective beamformers as a convex optimization problem. In Proceedings of the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 (pp. 77-80). Taipei, TW.

MLA:
Mabande, Edwin, Adrian Schad, and Walter Kellermann. "Design of robust superdirective beamformers as a convex optimization problem." Proceedings of the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, Taipei 2009. 77-80.

BibTeX: 

Last updated on 2019-08-05 at 18:08