特征融合的射频指纹识别方法

doi:10.12066/j.issn.1007-2861.1624

Abstract

Abstract:

Considering the intra-robustness and inter-difference of transmitters in a radio frequency fingerprinting (RFF) identification system, this paper fuses the second-order spectra, i.e., power spectral density and cross-power spectral density of signals as fingerprints, and uses a radial basis probabilistic neural network as the classifier. The classification performance of the wireless network in two different series has been evaluated in simulation experiments. Compared with other feature extraction methods and classifiers, it is demonstrated that accuracy of the proposed method makes a great improvement.

Key words: radial basis probabilistic neural network, second-order spectra, radio frequency fingerprinting (RFF) identification

LIU Yanping, TIAN Jinpeng, CHEN Yong. RF fingerprinting identification with feature fusion[J]. Journal of Shanghai University（Natural Science Edition）, 2017, 23(3): 408-413.

References

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RF fingerprinting identification with feature fusion

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