Publications-Detail

Robust Self-Localization of Microphone Arrays Using a Minimum Number of Acoustic Sources

Authors:
Schrammen, M. ,  Hamad, A. ,  Jax, P.
Book Title:
Proceedings of European Signal Processing Conference (EUSIPCO)
Organization:
EUSIPCO
Date:
Sep. 2019
DOI:
10.23919/EUSIPCO.2019.8903077
Language:
English

Abstract

Multi-microphone signal processing is becoming increasingly popular in
applications such as far-distant speech recognition or communication in
adverse environments. To deploy source localization or signal enhancing
algorithms like beamforming the locations of the microphones must be known.
One well-studied approach to retrieve the relative positions of the
microphones is based on time-difference-of-arrival (TDoA) measurements.
However, current approaches are restricted to scenarios with a large number
of sources or specific coherence assumptions. In this paper a non-iterative
approach based on orthogonal geometric projection (OGP), which is able to
perform a blind self-localization of the array in 2D with only two sources
at arbitrary positions, is presented and extended to estimate a 3D array
shape with only three sources. Furthermore, an efficient method for outlier
correction in the pairwise distance (PD) estimates is proposed, that
significantly reduces the position error.

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