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Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals

Flood, Gabrielle LU ; Heyden, Anders LU and Åström, Kalle LU (2019) 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018 In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11351 LNCS. p.116-138
Abstract

Pairwise comparison of sound and radio signals can be used to estimate the distance between two units that send and receive signals. In a similar way it is possible to estimate differences of distances by correlating two received signals. There are essentially two groups of such methods, namely methods that are robust to noise and reverberation, but give limited precision and sub-sample refinements that are more sensitive to noise, but also give higher precision when they are initialized close to the real translation. In this paper, we present stochastic models that can explain the precision limits of such sub-sample time-difference estimates. Using these models new methods are provided for precise estimates of time-differences as well... (More)

Pairwise comparison of sound and radio signals can be used to estimate the distance between two units that send and receive signals. In a similar way it is possible to estimate differences of distances by correlating two received signals. There are essentially two groups of such methods, namely methods that are robust to noise and reverberation, but give limited precision and sub-sample refinements that are more sensitive to noise, but also give higher precision when they are initialized close to the real translation. In this paper, we present stochastic models that can explain the precision limits of such sub-sample time-difference estimates. Using these models new methods are provided for precise estimates of time-differences as well as Doppler effects. The developed methods are evaluated and verified on both synthetic and real data.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Doppler effect, Sub-sample methods, Time-difference of arrival, Uncertainty measure
host publication
Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers
series title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
editor
di Baja, Gabriella Sanniti; Fred, Ana; De Marsico, Maria; ; and
volume
11351 LNCS
pages
23 pages
publisher
Springer Verlag
conference name
7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018
conference location
Funchal, Portugal
conference dates
2018-01-16 - 2018-01-18
external identifiers
  • scopus:85060089291
ISSN
1611-3349
0302-9743
ISBN
9783030054984
DOI
10.1007/978-3-030-05499-1_7
language
English
LU publication?
yes
id
accd2b07-96d1-4159-b3a7-79f530e45b45
date added to LUP
2019-01-30 08:21:01
date last changed
2019-02-20 11:45:26
@inproceedings{accd2b07-96d1-4159-b3a7-79f530e45b45,
  abstract     = {<p>Pairwise comparison of sound and radio signals can be used to estimate the distance between two units that send and receive signals. In a similar way it is possible to estimate differences of distances by correlating two received signals. There are essentially two groups of such methods, namely methods that are robust to noise and reverberation, but give limited precision and sub-sample refinements that are more sensitive to noise, but also give higher precision when they are initialized close to the real translation. In this paper, we present stochastic models that can explain the precision limits of such sub-sample time-difference estimates. Using these models new methods are provided for precise estimates of time-differences as well as Doppler effects. The developed methods are evaluated and verified on both synthetic and real data.</p>},
  author       = {Flood, Gabrielle and Heyden, Anders and Åström, Kalle},
  booktitle    = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
  editor       = {di Baja, Gabriella Sanniti and Fred, Ana and De Marsico, Maria},
  isbn         = {9783030054984},
  issn         = {1611-3349},
  keyword      = {Doppler effect,Sub-sample methods,Time-difference of arrival,Uncertainty measure},
  language     = {eng},
  location     = {Funchal, Portugal},
  pages        = {116--138},
  publisher    = {Springer Verlag},
  title        = {Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals},
  url          = {http://dx.doi.org/10.1007/978-3-030-05499-1_7},
  volume       = {11351 LNCS},
  year         = {2019},
}