Title :
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
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;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1660432