Radio frequency fingerprinting feature fusion based on multi-domain discriminant kernel canonical correlation analysis
Author:
Publisher
Science China Press., Co. Ltd.
Subject
Engineering (miscellaneous),General Computer Science
Link
https://engine.scichina.com/doi/pdf/EA10F4A1707A46D6AD40EE595BE5A33E
Reference38 articles.
1. Xie F, Wen H, Wu J. Data Augmentation for Radio Frequency Fingerprinting via Pseudo-Random Integration. IEEE Trans Emerg Top Comput Intell, 2020, 4: 276-286.
2. Ming-Wei Liu null, Doherty J F. Nonlinearity Estimation for Specific Emitter Identification in Multipath Channels. IEEE TransInformForensic Secur, 2011, 6: 1076-1085.
3. Ru X H, Gao C, Liu Z, et al. Emitter identification based on the structure of unintentional modulation. In: Proceedings of the 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2016. 998--1002.
4. Gok G, Alp Y K, Arikan O. A New Method for Specific Emitter Identification With Results on Real Radar Measurements. IEEE TransInformForensic Secur, 2020, 15: 3335-3346.
5. Gong J, Xu X, Lei Y. Unsupervised Specific Emitter Identification Method Using Radio-Frequency Fingerprint Embedded InfoGAN. IEEE TransInformForensic Secur, 2020, 15: 2898-2913.
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