收稿日期: 2015-03-04
网络出版日期: 2017-06-30
基金资助
国家自然科学基金重点项目面上资助项目(61171086); 上海大学创新基金资助项目(sdcx2012041)
RF fingerprinting identification with feature fusion
Received date: 2015-03-04
Online published: 2017-06-30
刘燕平, 田金鹏, 陈泳 . 特征融合的射频指纹识别方法[J]. 上海大学学报(自然科学版), 2017 , 23(3) : 408 -413 . DOI: 10.12066/j.issn.1007-2861.1624
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.
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