Improvements in HMM based spectral frequency line estimation

Author

Gunes, Tuncay ; Erdol, Nurgun

Author_Institution

Electr. Eng., Florida Atlantic Univ., Boca Raton, FL, USA

fYear

2006

fDate

4-8 Sept. 2006

Firstpage

1

Lastpage

5

Abstract

This paper considers the application of Hidden Markov Models to the problem of tracking frequency lines in spectrograms of strongly non-stationary signals such as encountered in aero-acoustics and sonar where tracking difficulties arise from low SNR and large variances associated with spectral estimates. In the proposed method, we introduce a novel method to determine the observation (measurement) likelihoods by interpolation between local maxima. We also show that use of low variance AutoRegressiveMultiTaper (ARMT) spectral estimates results in improved tracking. The frequency line is tracked using the Forward-Backward and Viterbi algorithms.

Keywords

autoregressive moving average processes; covariance analysis; frequency estimation; hidden Markov models; signal processing; HMM; Viterbi algorithms; autoregressivemultitaper spectral estimates; forward-backward algorithms; frequency lines; hidden Markov models; spectral frequency line estimation; spectrograms; Acoustics; Approximation methods; Europe; Hidden Markov models; Markov processes; Spectrogram; Time-frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2006 14th European

Conference_Location

Florence

ISSN

2219-5491

Type

conf

Filename

7071533