Non-Stationary Signal Classification Using Joint Frequency Analysis

Time-varying short-term spectral estimates have been successfully applied in many classification tasks. However, they are still insufficient for many non-stationary signals where time-varying information is useful. In this paper, we propose to improve the deficiencies of current short-term feature a...

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Bibliographic Details
Main Authors: Sukittanon, Somsak, Atlas, Les E, Pitton, James W, McLaughlin, Jack
Format: Report
Language:English
Subjects:
CLASSIFICATION
ESTIMATES
FEATURE EXTRACTION
FREQUENCY ANALYSIS
FREQUENCY ANALYZERS
FREQUENCY MODULATION
Miscellaneous Detection and Detectors
Radio Communications
Radiofrequency Wave Propagation
SIGNAL CLASSIFICATION
SIGNAL PROCESSING
SPECTRA
TIME
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Summary:Time-varying short-term spectral estimates have been successfully applied in many classification tasks. However, they are still insufficient for many non-stationary signals where time-varying information is useful. In this paper, we propose to improve the deficiencies of current short-term feature analysis by adding information to describe the time-varying behavior of the signals. Our proposed method, which is motivated by the human auditory system, can be applied to several non-stationary signal types. Real world communication signals were used for experimental verification. These experimental results, assessed with a conventional probabilistic classifier, showed significant improvement when the new features were added to short-term spectral estimates. Sponsored in part by the Air Force Research Laboratory (AFRL).