Publication | Closed Access
Real-World ADS-B signal recognition based on Radio Frequency Fingerprinting
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Citations
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References
2020
Year
Unknown Venue
EngineeringMachine LearningBiometricsInformation ForensicsImage ForensicsFingerprint AnalysisImage AnalysisData SciencePattern RecognitionAutomatic Dependent Surveillance-broadcastAircraft Identity VerificationIdentification MethodAutomatic IdentificationMachine VisionContour Stellar ImagesMultidimensional Signal ProcessingIdentity-based SecurityComputer ScienceDeep LearningSignal ProcessingComputer VisionRadio Frequency FingerprintingPattern Recognition Application
To meet the future needs of increasingly crowded airspace, the International Civil Aviation Organization (ICAO ) proposed to use the Automatic Dependent Surveillance-Broadcast (ADS-B ) to provide navigation and surveillance technology to solve the problems of security and capacity in the airspace. But ADS-B does not offer any authentication and encryption. So it is vulnerable to attacks by various illegal devices. A novel radiofrequency fingerprint (RFF ) recognition method of aircraft identity verification based on deep learning is proposed. The ADS-B signal captured by RTL-SDR is used for confirmation. The experimental results show that the fingerprint is called the Contour Stellar Images with a better recognition effect under different networks and different SNR.
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