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

Kowalczyk K, Habets E, Kellermann W, Naylor PA (2013)

Publication Language: English

Publication Status: Published

Publication Type: Journal article, Original article

Publication year: 2013

Journal

IEEE Signal Processing Letters Institute of Electrical and Electronics Engineers (IEEE)

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 20

Pages Range: 653-656

Article Number: 6512048

Journal Issue: 7

DOI: 10.1109/LSP.2013.2261059

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.

Authors with CRIS profile

Konrad Kowalczyk International Audio Laboratories Erlangen (AudioLabs) Emanuël Habets Professur für wahrnehmungsbasierte räumliche Audiosignalverarbeitung (AudioLabs) (Stiftungsprofessur) Walter Kellermann Professur für Signalverarbeitung

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB)

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://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.

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