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Acoustic Sensor Self-Localization: Models and Recent Results
Joint Authors
Lee, Bowon
Haddad, Diego B.
Lima, Markus V. S.
Martins, Wallace A.
Biscainho, Luiz W. P.
Nunes, Leonardo O.
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-22
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
The wide availability of mobile devices with embedded microphones opens up opportunities for new applications based on acoustic sensor localization (ASL).
Among them, this paper highlights mobile device self-localization relying exclusively on acoustic signals, but with previous knowledge of reference signals and source positions.
The problem of finding the sensor position is stated as a function of estimated times-of-flight (TOFs) or time-differences-of-flight (TDOFs) from the sound sources to the target microphone, and the main practical issues involved in TOF estimation are discussed.
Least-squares ASL solutions are introduced, followed by other strategies inspired by sound source localization solutions: steered-response power, which improves localization accuracy, and a new region-based search, which alleviates complexity.
A set of complementary techniques for further improvement of TOF/TDOF estimates are reviewed: sliding windows, matching pursuit, and TOF selection.
The paper proceeds with proposing a novel ASL method that combines most of the previous material, whose performance is assessed in a real-world example: in a typical lecture room, the method achieves accuracy better than 20 cm.
American Psychological Association (APA)
Haddad, Diego B.& Lima, Markus V. S.& Martins, Wallace A.& Biscainho, Luiz W. P.& Nunes, Leonardo O.& Lee, Bowon. 2017. Acoustic Sensor Self-Localization: Models and Recent Results. Wireless Communications and Mobile Computing،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1206203
Modern Language Association (MLA)
Haddad, Diego B.…[et al.]. Acoustic Sensor Self-Localization: Models and Recent Results. Wireless Communications and Mobile Computing No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1206203
American Medical Association (AMA)
Haddad, Diego B.& Lima, Markus V. S.& Martins, Wallace A.& Biscainho, Luiz W. P.& Nunes, Leonardo O.& Lee, Bowon. Acoustic Sensor Self-Localization: Models and Recent Results. Wireless Communications and Mobile Computing. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1206203
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206203