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Frequency Line Tracking in Spectrograms Using Hidden Markov Models
| Title: | Frequency Line Tracking in Spectrograms Using Hidden Markov Models. |
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| Name(s): |
Gunes, Tuncay Erdol, Nurgun, Thesis advisor Florida Atlantic University, Degree grantor |
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| Type of Resource: | text | |
| Genre: | Electronic Thesis Or Dissertation | |
| Date Created: | 2006 | |
| Date Issued: | 2006 | |
| Publisher: | Florida Atlantic University | |
| Place of Publication: | Boca Raton, Fla. | |
| Physical Form: | application/pdf | |
| Extent: | 73 p. | |
| Language(s): | English | |
| Abstract/Description: | One of the limiting factors restricting aircraft landings at maJor airports is the minimum spacing requirements due to vortex wake avoidance. If it can be shown that the separation requirements are too conservative, then it may be possible to increase the rate of landings on a given runway. During August/September 2003, NASA and the (United States Department of Transportation) USDOT sponsored a wake acoustics test at the Denver International Airport. The central instrument of the test was a large microphone phased array. Different types of aircrafts were recorded during landing and the acoustic data obtained was stored. From acoustic data the spectrograms were generated using the technique of AutoRegressive (AR) spectral estimation from multitaper autocorrelation estimates. Several sources of sound that are recorded in the audio files can be observed in the spectrograms. Some these signals, such as the noise generated from the aircraft engine can be identified easily because of their strength and the Doppler shift they undergo. In contrast to this, the wake vortex signal is weaker and does not exhibit a Doppler shift because it's stationary in space. Therefore it may not be identified easily because of the existence of stronger signals. The motive in our research is to develop methods to determine these strong signals that appear as spectral lines in the spectrogram. In the future, the results obtained in this work can be used to eliminate these strong signals from the spectrogram thus allowing us to see and identify wake vortex signal which is more important to us. | |
| Identifier: | FA00012525 (IID) | |
| Degree granted: | Thesis (M.S.)--Florida Atlantic University, 2006. | |
| Collection: | FAU Electronic Theses and Dissertations Collection | |
| Note(s): | College of Engineering and Computer Science | |
| Subject(s): |
Markov processes Economics--Mathematical models Wave structure function--Analysis Adaptive control systems Spectrum analysis |
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| Held by: | Florida Atlantic University Libraries | |
| Sublocation: | Digital Library | |
| Persistent Link to This Record: | http://purl.flvc.org/fau/fd/FA00012525 | |
| Use and Reproduction: | Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. | |
| Use and Reproduction: | http://rightsstatements.org/vocab/InC/1.0/ | |
| Host Institution: | FAU | |
| Is Part of Series: | Florida Atlantic University Digital Library Collections. |
