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

Gabrielle Flood; Anders Heyden; Kalle Åström

doi:10.1007/978-3-030-05499-1_7

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

Gabrielle Flood, Anders Heyden, Kalle Åström

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

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.

Originalspråk	engelska
Titel på värdpublikation	Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers
Redaktörer	Gabriella Sanniti di Baja, Ana Fred, Maria De Marsico
Förlag	Springer
Sidor	116-138
Antal sidor	23
ISBN (tryckt)	9783030054984
DOI	https://doi.org/10.1007/978-3-030-05499-1_7
Status	Published - 2019
Evenemang	7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018 - Madeira, Funchal, Portugal Varaktighet: 2018 jan. 16 → 2018 jan. 18

Publikationsserier

Namn	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volym	11351 LNCS
ISSN (tryckt)	0302-9743
ISSN (elektroniskt)	1611-3349

Konferens

Konferens	7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018
Förkortad titel	ICPRAM 2018
Land/Territorium	Portugal
Ort	Funchal
Period	2018/01/16 → 2018/01/18

Ämnesklassifikation (UKÄ)

Matematik

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10.1007/978-3-030-05499-1_7

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Mapping and Merging Using Sound and Vision: Automatic Calibration and Map Fusion with Statistical Deformations
Flood, G., 2021 dec. 10, Lund University / Centre for Mathematical Sciences /LTH. 238 s.
Forskningsoutput: Avhandling › Doktorsavhandling (sammanläggning)

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Flood, G., Heyden, A., & Åström, K. (2019). Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals. I G. S. di Baja, A. Fred, & M. De Marsico (Red.), Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers (s. 116-138). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11351 LNCS). Springer. https://doi.org/10.1007/978-3-030-05499-1_7

Flood, Gabrielle ; Heyden, Anders ; Åström, Kalle. / Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals. Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers. redaktör / Gabriella Sanniti di Baja ; Ana Fred ; Maria De Marsico. Springer, 2019. s. 116-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals",

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 as Doppler effects. The developed methods are evaluated and verified on both synthetic and real data.",

keywords = "Doppler effect, Sub-sample methods, Time-difference of arrival, Uncertainty measure",

author = "Gabrielle Flood and Anders Heyden and Kalle {\AA}str{\"o}m",

year = "2019",

doi = "10.1007/978-3-030-05499-1_7",

language = "English",

isbn = "9783030054984",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "116--138",

editor = "{di Baja}, {Gabriella Sanniti} and Ana Fred and {De Marsico}, Maria",

booktitle = "Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers",

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note = "7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018, ICPRAM 2018 ; Conference date: 16-01-2018 Through 18-01-2018",

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Flood, G , Heyden, A & Åström, K 2019, Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals. i GS di Baja, A Fred & M De Marsico (red), Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11351 LNCS, Springer, s. 116-138, 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018, Funchal, Portugal, 2018/01/16. https://doi.org/10.1007/978-3-030-05499-1_7

Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals. / Flood, Gabrielle ; Heyden, Anders ; Åström, Kalle.
Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers. red. / Gabriella Sanniti di Baja; Ana Fred; Maria De Marsico. Springer, 2019. s. 116-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11351 LNCS).

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

TY - GEN

T1 - Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals

AU - Flood, Gabrielle

AU - Heyden, Anders

AU - Åström, Kalle

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Doppler effect

KW - Sub-sample methods

KW - Time-difference of arrival

KW - Uncertainty measure

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DO - 10.1007/978-3-030-05499-1_7

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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T2 - 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018

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Flood G , Heyden A , Åström K. Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals. I di Baja GS, Fred A, De Marsico M, redaktörer, Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers. Springer. 2019. s. 116-138. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-05499-1_7

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

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Mapping and Merging Using Sound and Vision: Automatic Calibration and Map Fusion with Statistical Deformations

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