Analysis and implementation of the adaptive notch filter for frequency estimation

Sun Yuan Kung; D. V.Bhaskar Rao

doi:10.1109/ICASSP.1982.1171784

Analysis and implementation of the adaptive notch filter for frequency estimation

Sun Yuan Kung, D. V.Bhaskar Rao

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

This paper enhances some theoretical and implementation aspects of a constrained autoregressive moving average model, the notch filter model developed in [1] for the estimation of sinusoidal signals in additive, uncorrelated noise, colored or white. This model is shown to approximate the actual signal plus noise model. In addition, the parameter estimates obtained by minimization of the output power of the notch filter approximate the maximum likelihood estimate of the model parameters. The relationship of the notch filtering approach to the existing autoregressive and Pisarenke methods is established. Next, a scheme to combine fast convergence and unbiased estimation is suggested. Lastly, certain implementation aspects of the filter are considered and the method is shown to be amenable to parallel processing.

Original language	English (US)
Article number	1171784
Pages (from-to)	663-666
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	1982-May
DOIs	https://doi.org/10.1109/ICASSP.1982.1171784
State	Published - 1982
Externally published	Yes
Event	1982 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1982 - Paris, France Duration: May 3 1982 → May 5 1982

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP.1982.1171784

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title = "Analysis and implementation of the adaptive notch filter for frequency estimation",

abstract = "This paper enhances some theoretical and implementation aspects of a constrained autoregressive moving average model, the notch filter model developed in [1] for the estimation of sinusoidal signals in additive, uncorrelated noise, colored or white. This model is shown to approximate the actual signal plus noise model. In addition, the parameter estimates obtained by minimization of the output power of the notch filter approximate the maximum likelihood estimate of the model parameters. The relationship of the notch filtering approach to the existing autoregressive and Pisarenke methods is established. Next, a scheme to combine fast convergence and unbiased estimation is suggested. Lastly, certain implementation aspects of the filter are considered and the method is shown to be amenable to parallel processing.",

author = "Kung, {Sun Yuan} and Rao, {D. V.Bhaskar}",

note = "Publisher Copyright: {\textcopyright} 1982 IEEE.; 1982 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1982 ; Conference date: 03-05-1982 Through 05-05-1982",

year = "1982",

doi = "10.1109/ICASSP.1982.1171784",

language = "English (US)",

volume = "1982-May",

pages = "663--666",

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

issn = "1520-6149",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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TY - JOUR

T1 - Analysis and implementation of the adaptive notch filter for frequency estimation

AU - Kung, Sun Yuan

AU - Rao, D. V.Bhaskar

PY - 1982

Y1 - 1982

N2 - This paper enhances some theoretical and implementation aspects of a constrained autoregressive moving average model, the notch filter model developed in [1] for the estimation of sinusoidal signals in additive, uncorrelated noise, colored or white. This model is shown to approximate the actual signal plus noise model. In addition, the parameter estimates obtained by minimization of the output power of the notch filter approximate the maximum likelihood estimate of the model parameters. The relationship of the notch filtering approach to the existing autoregressive and Pisarenke methods is established. Next, a scheme to combine fast convergence and unbiased estimation is suggested. Lastly, certain implementation aspects of the filter are considered and the method is shown to be amenable to parallel processing.

AB - This paper enhances some theoretical and implementation aspects of a constrained autoregressive moving average model, the notch filter model developed in [1] for the estimation of sinusoidal signals in additive, uncorrelated noise, colored or white. This model is shown to approximate the actual signal plus noise model. In addition, the parameter estimates obtained by minimization of the output power of the notch filter approximate the maximum likelihood estimate of the model parameters. The relationship of the notch filtering approach to the existing autoregressive and Pisarenke methods is established. Next, a scheme to combine fast convergence and unbiased estimation is suggested. Lastly, certain implementation aspects of the filter are considered and the method is shown to be amenable to parallel processing.

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U2 - 10.1109/ICASSP.1982.1171784

DO - 10.1109/ICASSP.1982.1171784

M3 - Conference article

AN - SCOPUS:17444376922

SN - 1520-6149

VL - 1982-May

SP - 663

EP - 666

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

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

M1 - 1171784

T2 - 1982 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1982

Y2 - 3 May 1982 through 5 May 1982

ER -

Analysis and implementation of the adaptive notch filter for frequency estimation

Abstract

All Science Journal Classification (ASJC) codes

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