On Feature Based Automatic Classification of Single and Multitone Signals

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Executive Summary

The authors consider the problem of feature based automatic classification of single and multitone signals. Their objective is to extend existing blind demodulation techniques to multitone waveforms such as MIL-STD-188-110B (Appendix B) and OFDM, developing a capability to identify signal types based on short data records, and maintaining robustness to channel effects. In this paper, they report on the first phase of their approach, namely, building a coarse classifier for a range of single tone and multitone signals. Among the features considered by the coarse classifier are those based on trigonometric moments and higher order statistics of the instantaneous frequencies of the received signal.

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