"RF-DNA" Fingerprinting for Antenna Classification
Document Type
Article
Publication Date
3-10-2015
Abstract
Device classification is important for many applications such as industrial quality controls, through-wall imaging, and network security. A novel approach to detection is proposed using a random noise radar (RNR), coupled with Radio Frequency “Distinct Native Attribute (RF-DNA)” fingerprinting processing algorithms to non-destructively interrogate microwave devices. RF-DNA has previously demonstrated “serial number” discrimination of passive Radio Frequency (RF) emissions such as Orthogonal Frequency Division Multiplexed (OFDM) signals, Worldwide Interoperability for Microwave Access (WiMAX) signals and others with classification accuracies above 80% using a Multiple Discriminant Analysis/Maximum Likelihood (MDAML) classifier. This approach proposes to couple the classification successes of the RF-DNA fingerprint processing with a non-destructive active interrogation waveform. An Ultra Wideband (UWB) noise waveform is uniquely suitable as an active interrogation method since it will not cause damage to sensitive microwave components and multiple RNRs can operate simultaneously in close proximity, allowing for significant parallelization of detection systems.
Source Publication
IEEE Antennas and Wireless Propagation Letters (ISSN 1536-1225)
Recommended Citation
M. W. Lukacs, A. J. Zeqolari, P. J. Collins and M. A. Temple, "“RF-DNA” Fingerprinting for Antenna Classification," in IEEE Antennas and Wireless Propagation Letters, vol. 14, pp. 1455-1458, 2015, doi: 10.1109/LAWP.2015.2411608.
Comments
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Co-author Mathew Lukacs was an AFIT PhD student at the time of this article. (DTIC R&E: AD1018264, September 2016 graduate)