Blind Calibration for Acoustic Vector Sensor Arrays

Krishnaprasad Nambur Ramamohan; Sundeep Prabhakar Chepuri; Daniel Fernandez Comesana; Graciano Carrillo Pousa; Geert Leus

doi:10.1109/ICASSP.2018.8462035

Blind Calibration for Acoustic Vector Sensor Arrays

Krishnaprasad Nambur Ramamohan, Sundeep Prabhakar Chepuri, Daniel Fernandez Comesana, Graciano Carrillo Pousa, Geert Leus

Signal Processing Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

8 Citations (Scopus)

13 Downloads (Pure)

Abstract

In this paper, we present a calibration algorithm for acoustic vector sensors arranged in a uniform linear array configuration. To do so, we do not use a calibrator source, instead we leverage the Toeplitz blocks present in the data covariance matrix. We develop linear estimators for estimating sensor gains and phases. Further, we discuss the differences of the presented blind calibration approach for acoustic vector sensor arrays in comparison with the approach for acoustic pressure sensor arrays. In order to validate the proposed blind calibration algorithm, simulation results for direction-of-arrival (DOA) estimation with an uncalibrated and calibrated uniform linear array based on minimum variance distortion less response and multiple signal classification algorithms are presented. The calibration performance is analyzed using the Cramér-Rao lower bound of the DOA estimates.

Original language	English
Title of host publication	2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	3544-3548
Number of pages	5
ISBN (Electronic)	978-1-5386-4658-8
ISBN (Print)	978-1-5386-4659-5
DOIs	https://doi.org/10.1109/ICASSP.2018.8462035
Publication status	Published - 2018
Event	2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018: Signal Processing and Artificial Intelligence: Changing the World - Calgary Telus Convention Center (CTCC), Calgary, Canada Duration: 15 Apr 2018 → 20 Apr 2018 https://2018.ieeeicassp.org

Conference

Conference	2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
Country/Territory	Canada
City	Calgary
Period	15/04/18 → 20/04/18
Internet address	https://2018.ieeeicassp.org

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Acoustic vector sensor
Direction-of-arrival estimation
Gain estimation
Phase estimation
Self calibration

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10.1109/ICASSP.2018.8462035

Blind_Calibration_for_Acoustic_Vector_Sensor_ArraysFinal published version, 729 KB

Cite this

@inproceedings{b5a9fb9addc7440d963b0f6a48cc1002,

title = "Blind Calibration for Acoustic Vector Sensor Arrays",

abstract = "In this paper, we present a calibration algorithm for acoustic vector sensors arranged in a uniform linear array configuration. To do so, we do not use a calibrator source, instead we leverage the Toeplitz blocks present in the data covariance matrix. We develop linear estimators for estimating sensor gains and phases. Further, we discuss the differences of the presented blind calibration approach for acoustic vector sensor arrays in comparison with the approach for acoustic pressure sensor arrays. In order to validate the proposed blind calibration algorithm, simulation results for direction-of-arrival (DOA) estimation with an uncalibrated and calibrated uniform linear array based on minimum variance distortion less response and multiple signal classification algorithms are presented. The calibration performance is analyzed using the Cram{\'e}r-Rao lower bound of the DOA estimates.",

keywords = "Acoustic vector sensor, Direction-of-arrival estimation, Gain estimation, Phase estimation, Self calibration",

author = "Ramamohan, {Krishnaprasad Nambur} and Chepuri, {Sundeep Prabhakar} and Comesana, {Daniel Fernandez} and Pousa, {Graciano Carrillo} and Geert Leus",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 : Signal Processing and Artificial Intelligence: Changing the World ; Conference date: 15-04-2018 Through 20-04-2018",

year = "2018",

doi = "10.1109/ICASSP.2018.8462035",

language = "English",

isbn = "978-1-5386-4659-5",

pages = "3544--3548",

booktitle = "2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings",

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url = "https://2018.ieeeicassp.org",

}

Ramamohan, KN, Chepuri, SP, Comesana, DF, Pousa, GC & Leus, G 2018, Blind Calibration for Acoustic Vector Sensor Arrays. in 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings., 8462035, IEEE, Piscataway, NJ, pp. 3544-3548, 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018, Calgary, Canada, 15/04/18. https://doi.org/10.1109/ICASSP.2018.8462035

Blind Calibration for Acoustic Vector Sensor Arrays. / Ramamohan, Krishnaprasad Nambur; Chepuri, Sundeep Prabhakar; Comesana, Daniel Fernandez et al.
2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Piscataway, NJ: IEEE, 2018. p. 3544-3548 8462035.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Ramamohan, Krishnaprasad Nambur

AU - Chepuri, Sundeep Prabhakar

AU - Comesana, Daniel Fernandez

AU - Pousa, Graciano Carrillo

AU - Leus, Geert

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2018

Y1 - 2018

N2 - In this paper, we present a calibration algorithm for acoustic vector sensors arranged in a uniform linear array configuration. To do so, we do not use a calibrator source, instead we leverage the Toeplitz blocks present in the data covariance matrix. We develop linear estimators for estimating sensor gains and phases. Further, we discuss the differences of the presented blind calibration approach for acoustic vector sensor arrays in comparison with the approach for acoustic pressure sensor arrays. In order to validate the proposed blind calibration algorithm, simulation results for direction-of-arrival (DOA) estimation with an uncalibrated and calibrated uniform linear array based on minimum variance distortion less response and multiple signal classification algorithms are presented. The calibration performance is analyzed using the Cramér-Rao lower bound of the DOA estimates.

AB - In this paper, we present a calibration algorithm for acoustic vector sensors arranged in a uniform linear array configuration. To do so, we do not use a calibrator source, instead we leverage the Toeplitz blocks present in the data covariance matrix. We develop linear estimators for estimating sensor gains and phases. Further, we discuss the differences of the presented blind calibration approach for acoustic vector sensor arrays in comparison with the approach for acoustic pressure sensor arrays. In order to validate the proposed blind calibration algorithm, simulation results for direction-of-arrival (DOA) estimation with an uncalibrated and calibrated uniform linear array based on minimum variance distortion less response and multiple signal classification algorithms are presented. The calibration performance is analyzed using the Cramér-Rao lower bound of the DOA estimates.

KW - Acoustic vector sensor

KW - Direction-of-arrival estimation

KW - Gain estimation

KW - Phase estimation

KW - Self calibration

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M3 - Conference contribution

AN - SCOPUS:85054198674

SN - 978-1-5386-4659-5

SP - 3544

EP - 3548

BT - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings

PB - IEEE

CY - Piscataway, NJ

T2 - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018

Y2 - 15 April 2018 through 20 April 2018

ER -

Blind Calibration for Acoustic Vector Sensor Arrays

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Keywords

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