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Summary: ON FEATURE BASED AUTOMATIC CLASSIFICATION OF SINGLE AND
MULTITONE SIGNALS
Arindam K. Das, Payman Arabshahi, Tim Wen
Applied Physics Laboratory
University of Washington, Box 355640, Seattle, WA 98195, USA.
email: {arindam, payman, tim}@apl.washington.edu
Wei Su
Us Army CERDEC, AMSRD-CER-IW-IE
Fort Monmouth, NJ 07703, USA.
email: Wei.Su@us.army.mil
ABSTRACT
We consider the problem of feature based automatic clas-
sification of single and multitone signals. Our objective is
to extend existing blind demodulation techniques to multi-
tone 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 robust-
ness to channel effects. In this paper, we report on the first
phase of our approach, namely, building a coarse classifier
for a range of single tone and multitone signals. Among
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