A Low-Cost Robust Distributed Linearly Constrained Beamformer for Wireless Acoustic Sensor Networks with Arbitrary Topology

Andreas Koutrouvelis, Thomas William Sherson, Richard Heusdens, Richard C. Hendriks

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
11 Downloads (Pure)

Abstract

We propose a new robust distributed linearly constrained beamformer which utilizes a set of linear equality constraints to reduce the cross power spectral density matrix to a block-diagonal form. The proposed beamformer has a convenient objective function for use in arbitrary distributed network topologies while having identical performance to a centralized implementation. Moreover, the new optimization problem is robust to relative acoustic transfer function (RATF) estimation errors and to target activity detection (TAD) errors. Two variants of the proposed beamformer are presented and evaluated in the context of multi-microphone speech enhancement in a wireless acoustic sensor network, and are compared with other state-of-the-art distributed beamformers in terms of communication costs and robustness to RATF estimation errors and TAD errors.

Original languageEnglish
Pages (from-to)1434-1448
Number of pages15
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Volume26
Issue number8
DOIs
Publication statusPublished - 2018

Keywords

  • Distributed beamforming
  • Estimation error
  • LCMV
  • Microphones
  • MVDR
  • Network topology
  • Noise measurement
  • Reverberation
  • robust beamforming
  • Robustness
  • speech enhancement
  • WASN

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