Blind system identification using sparse learning for TDOA estimation of room reflections

Journal article
(Original article)


Publication Details

Author(s): Kowalczyk K, Habets E, Kellermann W, Naylor PA
Journal: IEEE Signal Processing Letters
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Publication year: 2013
Volume: 20
Journal issue: 7
Pages range: 653-656
ISSN: 1070-9908


Abstract


Localization of early room reflections can be achieved by estimating the time-differences-of-arrival (TDOAs) of reflected waves between elements of a microphone array. For an unknown source, we propose to apply sparse blind system identification (BSI) methods to identify the acoustic impulse responses, from which the TDOAs of temporally sparse reflections are estimated. The proposed time-and frequency-domain adaptive algorithms based on crossrelation formulation are regularized by incorporating an l-norm sparseness constraint, which is realized using a split Bregman method. These algorithms are shown to outperform standard crossrelation-based BSI techniques when estimating TDOAs of reflections in the presence of background noise. © 1994-2012 IEEE.



FAU Authors / FAU Editors

Habets, Emanuël Prof. Dr.
Professur für wahrnehmungsbasierte räumliche Audiosignalverarbeitung (AudioLabs) (Stiftungsprofessur)
Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik
Kowalczyk, Konrad Dr.
International Audio Laboratories Erlangen (AudioLabs)


How to cite

APA:
Kowalczyk, K., Habets, E., Kellermann, W., & Naylor, P.A. (2013). Blind system identification using sparse learning for TDOA estimation of room reflections. IEEE Signal Processing Letters, 20(7), 653-656. https://dx.doi.org/10.1109/LSP.2013.2261059

MLA:
Kowalczyk, Konrad, et al. "Blind system identification using sparse learning for TDOA estimation of room reflections." IEEE Signal Processing Letters 20.7 (2013): 653-656.

BibTeX: 

Last updated on 2018-19-04 at 03:34