A Low-Cost Robust Distributed Linearly Constrained Beamformer for Wireless Acoustic Sensor Networks with Arbitrary Topology
share
We propose a new robust distributed linearly constrained beamformer (BF) which utilizes a set of linear equality constraints to reduce the cross power spectral density matrix to a block-diagonal form. The proposed BF 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 steering vector mismatches (SVMs) and to voice activity detection errors. Two variants of the proposed BF 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 BFs in terms of communication costs and robustness to SVMs.
READ FULL TEXT