Paper
6 April 1995 Novel identification of intercepted signals from unknown radio transmitters
Howard C. Choe, Clark E. Poole, Andrea M. Yu, Harold H. Szu
Author Affiliations +
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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Howard C. Choe, Clark E. Poole, Andrea M. Yu, and Harold H. Szu "Novel identification of intercepted signals from unknown radio transmitters", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); https://doi.org/10.1117/12.205415
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CITATIONS
Cited by 55 scholarly publications.
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KEYWORDS
Transmitters

Wavelets

Feature extraction

Antennas

Receivers

Neural networks

Signal analyzers

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