Automatic robust adaptive beamforming via ridge regression
2007 (English)In: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol II, Pts 1-3, 2007, 965-968 p.Conference paper (Refereed)
In this paper we derive a class of new parameter free robust adaptive beamformers using the generalized sidelobe canceler reparameterization of the Capon beamformer. In this parameterization the minimum variance beamformer is obtained as the solution of a linear least squares problem. In the case of an inaccurate steering vector and/or few data snapshots this marginally overdetermined system gives an ill fit causing signal cancellation in the standard minimum variance solution. By regularizing the problem using ridge regression techniques we get a whole class of robust adaptive beamformers, none of which requires the choice of a user parameter. We also propose a novel empirical Bayes-based ridge regression technique. The performance is compared to other robust adaptive beamformers.
Place, publisher, year, edition, pages
2007. 965-968 p.
, International Conference on Acoustics Speech and Signal Processing (ICASSP), ISSN 1520-6149 ; 2
minimum variance beamforming, Capon beamforming, robust beamforming, ridge regression, regularization
Engineering and Technology
IdentifiersURN: urn:nbn:se:uu:diva-18255ISI: 000248908100242OAI: oai:DiVA.org:uu-18255DiVA: diva2:46027
32nd IEEE International Conference on Acoustics, Speech and Signal Processing Honolulu, HI, APR 15-20, 2007
Student Paper Award Winner: Honorary Mention2007-04-242007-04-242011-04-14Bibliographically approved