HMM Based Spectral Frequency Line Tracking: Improvements and New Results

Author

Gunes, Tuncay ; Erdol, Nurgun

Author_Institution

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

Volume

2

fYear

2006

fDate

14-19 May 2006

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 algorithm

Keywords

autoregressive processes; hidden Markov models; interpolation; sonar signal processing; spectral analysis; HMM; aero-acoustics; autoregressivemultitaper; forward-backward algorithm; hidden Markov models; interpolation; nonstationary signals; sonar; spectral frequency line tracking; spectrograms; Aircraft; Autocorrelation; Character generation; Frequency estimation; Hidden Markov models; Probability distribution; Spectrogram; State estimation; Statistical analysis; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1660432

Filename

1660432