DocumentCode
1487468
Title
Frequency line tracking using hidden Markov models
Author
Streit, Roy L. ; Barrett, Ross F.
Author_Institution
Defence Sci, & Technol. Organ., Salisbury, SA, Australia
Volume
38
Issue
4
fYear
1990
fDate
4/1/1990 12:00:00 AM
Firstpage
586
Lastpage
598
Abstract
Frequency cells comprising a subset, or gate, of the spectral bins from fast Fourier transform (FFT) processing are identified with the states of the hidden Markov chain. An additional zero state is included to allow for the possibility of track initiation and termination. Analytic expressions for the basic parameters of the hidden Markov model (HMM) are obtained in terms of physically meaningful quantities, and optimization of the HMM tracker is discussed. A measurement sequence based on a simple threshold detector forms the input to the tracker. The outputs of the HMM tracker are a discrete Viterbi track, a gate occupancy probability function, and a continuous mean cell occupancy track. The latter provides an estimate of the mean signal frequency as a function of time. The performance of the HMM tracker is evaluated for two sets of simulated data. The HMM tracker is compared to earlier, related trackers, and possible extensions are discussed
Keywords
Markov processes; fast Fourier transforms; signal processing; spectral analysis; tracking; FFT; HMM tracker; discrete Viterbi track; fast Fourier transform; frequency cells; frequency line tracking; gate occupancy probability function; hidden Markov chain; hidden Markov models; mean cell occupancy track; mean signal frequency; measurement sequence; signal processing; spectral analysis; spectral bins; threshold detector; Australia; Frequency estimation; Hidden Markov models; Laboratories; Radar signal processing; Radar tracking; Random variables; Signal processing algorithms; Speech; Weapons;
fLanguage
English
Journal_Title
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
0096-3518
Type
jour
DOI
10.1109/29.52700
Filename
52700
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