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Erschienen in: Autonomous Robots 2/2020

31.08.2019

Asynchronous microphone arrays calibration and sound source tracking

verfasst von: Daobilige Su, Teresa Vidal-Calleja, Jaime Valls Miro

Erschienen in: Autonomous Robots | Ausgabe 2/2020

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Abstract

In this paper, we proposed an optimisation method to solve the problem of sound source localisation and calibration of an asynchronous microphone array. This method is based on the graph-based formulation of the simultaneous localisation and mapping problem. In this formulation, a moving sound source is considered to be observed from a static microphone array. Traditional approaches for sound source localisation rely on the well-known geometrical information of the array and synchronous readings of the audio signals. Recent work relaxed these two requirements by estimating the temporal offset between pair of microphones based on the assumption that the clock timing of each microphone is exactly the same. This assumption requires the sound cards to be identically manufactured, which in practice is not possible to achieve. Hereby an approach is proposed to jointly estimate the array geometrical information, time offset and clock difference/drift rate of each microphone together with the location of a moving sound source. In addition, an observability analysis of the system is performed to investigate the most suitable configuration for sound source localisation. Simulation and experimental results are presented, which prove the effectiveness of the proposed methodology.

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Fußnoten
1
Note that the main difference with a standard landmark-pose SLAM system is that here all the microphones are “observed” at all times. In a standard SLAM system only part of the landmarks are observed at any time. This fact allows the microphone array to be treated as a single landmark with a large state that contains locations of all microphones. However, the same solution can be achieved if the microphones are considered independently.
 
2
Note that other motion models, such as constant velocity model, can be applied as long as it describes the motion of the sound source properly.
 
3
Note that uncertainties of microphone locations do not directly related to minimum eigenvalues of sub FIMs corresponding to individual microphones, due to: (1) Minimum eigenvalues of sub FIMs corresponding to individual microphones related to not only locations but also starting time offsets and clock differences of microphones. (2) Uncertainties of microphone locations depend on relative distance to microphone 1, which is fixed to the origin of the coordinates as a reference. This means microphones close to microphone 1 have smaller uncertainties on their estimated locations. In comparison, minimum eigenvalues of sub FIMs corresponding to individual microphones do not depend on distance to microphone 1.
 
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Metadaten
Titel
Asynchronous microphone arrays calibration and sound source tracking
verfasst von
Daobilige Su
Teresa Vidal-Calleja
Jaime Valls Miro
Publikationsdatum
31.08.2019
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 2/2020
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-019-09885-w

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