Instantaneous frequency estimation using sequential Bayesian techniques

Ying Li; Antonia Papandreou-Suppappola; Darryl Morrell

doi:10.1109/ACSSC.2006.354812

Instantaneous frequency estimation using sequential Bayesian techniques

Ying Li, Antonia Papandreou-Suppappola, Darryl Morrell

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

The online estimation of the instantaneous frequency (IF) of time-varying (TV) signals with highly nonlinear phase functions is a challenging problem. In this paper, we propose an IF estimation method using Bayesian techniques, which combines particle filtering and Markov Chain Monte Carlo (MCMC) methods, to sequentially estimate highly nonlinear TV frequency variations as piecewise linear functions. Simultaneously applying parameter estimation and model selection, the new technique is extended to the IF estimation of multicomponent signals. Using simulations, we demonstrate the performance of our approach for different signals and environments.

Original language	English (US)
Title of host publication	Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages	569-573
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2006.354812
State	Published - 2006
Event	40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States Duration: Oct 29 2006 → Nov 1 2006

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)	1058-6393

Other

Other	40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
Country/Territory	United States
City	Pacific Grove, CA
Period	10/29/06 → 11/1/06

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

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10.1109/ACSSC.2006.354812

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Li, Y., Papandreou-Suppappola, A., & Morrell, D. (2006). Instantaneous frequency estimation using sequential Bayesian techniques. In Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06 (pp. 569-573). Article 4176622 (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2006.354812

Instantaneous frequency estimation using sequential Bayesian techniques. / Li, Ying; Papandreou-Suppappola, Antonia ; Morrell, Darryl.
Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06. 2006. p. 569-573 4176622 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, Y, Papandreou-Suppappola, A & Morrell, D 2006, Instantaneous frequency estimation using sequential Bayesian techniques. in Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06., 4176622, Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 569-573, 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06, Pacific Grove, CA, United States, 10/29/06. https://doi.org/10.1109/ACSSC.2006.354812

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AB - The online estimation of the instantaneous frequency (IF) of time-varying (TV) signals with highly nonlinear phase functions is a challenging problem. In this paper, we propose an IF estimation method using Bayesian techniques, which combines particle filtering and Markov Chain Monte Carlo (MCMC) methods, to sequentially estimate highly nonlinear TV frequency variations as piecewise linear functions. Simultaneously applying parameter estimation and model selection, the new technique is extended to the IF estimation of multicomponent signals. Using simulations, we demonstrate the performance of our approach for different signals and environments.

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Instantaneous frequency estimation using sequential Bayesian techniques

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