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Proceedings Paper

Novel identification of intercepted signals from unknown radio transmitters
Author(s): Howard C. Choe; Clark E. Poole; Andrea M. Yu; Harold H. Szu
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Paper Abstract

We present a methodology for classifying and/or identifying unknown radio transmitters by analyzing turn-on transient signals. Since an expedited signal classification and identification is desirable, we developed an automated, fast signal classification and identification method using wavelet-based feature extraction combined with an artificial neural network (ANN). The environment we considered is that there are n radio frequency (rf) transmitters given m finite duration signals (m > n, several signals may be emitted from the same transmitter). We preprocess unknown transient signals using wavelet decomposition and extract multiresolution features (statistical and energy content) to provide efficient signal characterization. An ANN, trained on known signals and selected wavelets, is then used for classifying and identifying the extracted feature characteristics of the unknown signals. Our wavelet preprocessing combined with the ANN provide a robust and adaptive classifier and identifier. We also provide an example of transmitter classification and identification using transient signals collected from three different transmitters.

Paper Details

Date Published: 6 April 1995
PDF: 14 pages
Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); doi: 10.1117/12.205415
Show Author Affiliations
Howard C. Choe, Battelle Memorial Institute (United States)
Clark E. Poole, Federal Communications Commission (United States)
Andrea M. Yu, Syracuse Research Corp. (United States)
Harold H. Szu, Naval Surface Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 2491:
Wavelet Applications II
Harold H. Szu, Editor(s)

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