Observability Analysis of Graph SLAM-Based Joint Calibration of Multiple Microphone Arrays and Sound Source Localization

He, Y; Wang, J; Su, D; Nakadai, K; Wu, J; Huang, S; Li, Y; Kong, H

Observability Analysis of Graph SLAM-Based Joint Calibration of Multiple Microphone Arrays and Sound Source Localization

He, Y Wang, J Su, D Nakadai, K Wu, J Huang, S

Li, Y Kong, H

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2023 IEEE/SICE International Symposium on System Integration (SII), 2023, 00
Issue Date:: 2023-02-15

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Field	Value	Language
dc.contributor.author	He, Y
dc.contributor.author	Wang, J
dc.contributor.author	Su, D
dc.contributor.author	Nakadai, K
dc.contributor.author	Wu, J
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178
dc.contributor.author	Li, Y
dc.contributor.author	Kong, H
dc.date	2023-01-17
dc.date.accessioned	2023-11-06T05:07:40Z
dc.date.available	2023-11-06T05:07:40Z
dc.date.issued	2023-02-15
dc.identifier.citation	2023 IEEE/SICE International Symposium on System Integration (SII), 2023, 00
dc.identifier.isbn	9798350398687
dc.identifier.issn	2474-2317
dc.identifier.uri	http://hdl.handle.net/10453/173046
dc.description.abstract	Multiple microphone arrays have many applications in robot audition including sound source localization audio scene perception and analysis etc However accurate calibration of multiple microphone arrays remains a challenge because there are many unknown parameters to be identified including the Euler angles geometry asynchronous factors between the microphone arrays This paper is concerned with joint calibration of multiple microphone arrays and sound source localization using graph simultaneous localization and mapping SLAM By using a Fisher information matrix FIM approach we focus on the observability analysis of the graph SLAM framework for the above mentioned calibration problem We thoroughly investigate the identifiability of the unknown parameters including the Euler angles geometry asynchronous effects between the microphone arrays and the sound source locations We establish necessary sufficient conditions under which the FIM and the Jacobian matrix have full column rank which implies the identifiability of the unknown parameters These conditions are closely related to the variation in the motion of the sound source and the configuration of microphone arrays and have intuitive and physical interpretations We also discover several scenarios where the unknown parameters are not uniquely identifiable All theoretical findings are demonstrated using simulation data
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2023 IEEE/SICE International Symposium on System Integration (SII)
dc.relation.ispartof	2023 IEEE/SICE International Symposium on System Integration
dc.relation.ispartofseries	IEEE/SICE International Symposium on System Integration
dc.relation.isbasedon	10.1109/sii55687.2023.10039204
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Observability Analysis of Graph SLAM-Based Joint Calibration of Multiple Microphone Arrays and Sound Source Localization
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Atlanta, GA, USA
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - RI - Robotics Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2023-11-06T05:07:38Z
pubs.finish-date	2023-01-20
pubs.publication-status	Published
pubs.start-date	2023-01-17
pubs.volume	00

Abstract:

Multiple microphone arrays have many applications in robot audition including sound source localization audio scene perception and analysis etc However accurate calibration of multiple microphone arrays remains a challenge because there are many unknown parameters to be identified including the Euler angles geometry asynchronous factors between the microphone arrays This paper is concerned with joint calibration of multiple microphone arrays and sound source localization using graph simultaneous localization and mapping SLAM By using a Fisher information matrix FIM approach we focus on the observability analysis of the graph SLAM framework for the above mentioned calibration problem We thoroughly investigate the identifiability of the unknown parameters including the Euler angles geometry asynchronous effects between the microphone arrays and the sound source locations We establish necessary sufficient conditions under which the FIM and the Jacobian matrix have full column rank which implies the identifiability of the unknown parameters These conditions are closely related to the variation in the motion of the sound source and the configuration of microphone arrays and have intuitive and physical interpretations We also discover several scenarios where the unknown parameters are not uniquely identifiable All theoretical findings are demonstrated using simulation data

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http://hdl.handle.net/10453/173046