2015 IEEE Global Communications Conference (GLOBECOM) · 2015 · 28 citations · 13 references
EngineeringComputer EngineeringElectrical EngineeringFeature EngineeringTime Series AnalysisWireless CommunicationsHilbert Space FormalismSignal Detection TheorySignal ProcessingSpectral AnalysisHilbert TransformHilbert-huang TransformIdentificationMomentsRadio Frequency FingerprintingSignalsSpectral Feature DetectionSpectral Feature Extraction
A novel approach for specific emitter identification using Hilbert spectrum is proposed for both single-hop and relaying scenarios. In particular, two features, i.e., the energy entropy and color moments, are extracted from the Hilbert spectrum of the signal of interest as identification features. The spectrum is obtained through the Hilbert-Huang transform, which is a powerful tool for the analysis of non-linear and nonstationary signals by decomposing them into a set of intrinsic mode functions. The identification task is solved by applying the support vector machine. We further extend the identification problem to a relaying scenario, in which the fingerprint of different emitters may be contaminated by the relay's fingerprints. To the best of our knowledge, this case has not been investigated so far in the literature. At last, simulation results validate that the proposed approach can effectively cope with the specific emitter identification problems in both single-hop and relaying scenarios.
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