On cross correlation based discrete time delay estimation

Lei Zhang; Xiaolin Wu

doi:10.1109/ICASSP.2005.1416175

On cross correlation based discrete time delay estimation

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

24 Citations (Scopus)

Abstract

Cross correlation function (CCF) is a powerful tool in time delay estimation and parabola functions are widely used as parametric models of it. However, no study has been done on the accuracy of the parabola approximation of CCF. In this paper we analyze the CCF of multi-sensors and derive the analytic forms of CCF for the stationary processes of exponential auto-correlation function and with respect to two important types of sensor kernels. We demonstrate that the Gaussian function is a better and more robust approximation of CCF than the parabola in these cases. This new approach leads to higher precision in time delay estimation using the CCF peak locating strategy.

Original language	English
Title of host publication	2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions
Publisher	IEEE
Volume	IV
ISBN (Print)	0780388747, 9780780388741
DOIs	https://doi.org/10.1109/ICASSP.2005.1416175
Publication status	Published - 1 Jan 2005
Externally published	Yes
Event	2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States Duration: 18 Mar 2005 → 23 Mar 2005

Conference

Conference	2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/Territory	United States
City	Philadelphia, PA
Period	18/03/05 → 23/03/05

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

More information

10.1109/ICASSP.2005.1416175

Cite this

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abstract = "Cross correlation function (CCF) is a powerful tool in time delay estimation and parabola functions are widely used as parametric models of it. However, no study has been done on the accuracy of the parabola approximation of CCF. In this paper we analyze the CCF of multi-sensors and derive the analytic forms of CCF for the stationary processes of exponential auto-correlation function and with respect to two important types of sensor kernels. We demonstrate that the Gaussian function is a better and more robust approximation of CCF than the parabola in these cases. This new approach leads to higher precision in time delay estimation using the CCF peak locating strategy.",

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Zhang, L & Wu, X 2005, On cross correlation based discrete time delay estimation. in 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions. vol. IV, 1416175, IEEE, 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05, Philadelphia, PA, United States, 18/03/05. https://doi.org/10.1109/ICASSP.2005.1416175

On cross correlation based discrete time delay estimation. / Zhang, Lei; Wu, Xiaolin.
2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions. Vol. IV IEEE, 2005. 1416175.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AB - Cross correlation function (CCF) is a powerful tool in time delay estimation and parabola functions are widely used as parametric models of it. However, no study has been done on the accuracy of the parabola approximation of CCF. In this paper we analyze the CCF of multi-sensors and derive the analytic forms of CCF for the stationary processes of exponential auto-correlation function and with respect to two important types of sensor kernels. We demonstrate that the Gaussian function is a better and more robust approximation of CCF than the parabola in these cases. This new approach leads to higher precision in time delay estimation using the CCF peak locating strategy.

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ER -

On cross correlation based discrete time delay estimation

Abstract

Conference

ASJC Scopus subject areas

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