Detection of frequency‐hopping radio frequency‐switch transients

2014 ◽  
Vol 50 (13) ◽  
pp. 956-957 ◽  
Author(s):  
Yingjun Yuan ◽  
Zhitao Huang ◽  
Xiang Wang
Keyword(s):  
Radio Frequency ◽  
Frequency Hopping ◽  
Radio Frequency Switch

Sub-nanosecond-speed frequency-reconfigurable photonic radio frequency switch using a silicon modulator

2020 ◽  
Vol 8 (6) ◽  
pp. 852
Author(s):  
Yiwei Xie ◽  
Leimeng Zhuang ◽  
Pengcheng Jiao ◽  
Daoxin Dai
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Switch ◽  
Silicon Modulator

Functional processing of wideband radio frequency hopping signals

2007 ◽  
Vol 50 (7) ◽  
pp. 399-400
Author(s):  
V. B. Bobkov ◽  
V. V. Danilov ◽  
V. I. Mikityuk ◽  
E. N. Smirnov ◽  
A. A. Skulskii ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Frequency Hopping ◽  
Wideband Radio

Lubrication of microelectromechanical systems radio frequency switch contacts using self-assembled monolayers

2007 ◽  
Vol 102 (2) ◽  
pp. 024903 ◽  
Author(s):  
Steven T. Patton ◽  
Kalathil C. Eapen ◽  
Jeffrey S. Zabinski ◽  
Jeffrey H. Sanders ◽  
Andrey A. Voevodin
Keyword(s):  
Radio Frequency ◽  
Microelectromechanical Systems ◽  
Self Assembled Monolayers ◽  
Assembled Monolayers ◽  
Radio Frequency Switch ◽  
Self Assembled

scholarly journals Radio Frequency Fingerprinting for Frequency Hopping Emitter Identification

2021 ◽  
Vol 11 (22) ◽  
pp. 10812
Author(s):  
Jusung Kang ◽  
Younghak Shin ◽  
Hyunku Lee ◽  
Jintae Park ◽  
Heungno Lee
Keyword(s):  
Radio Frequency ◽  
Spread Spectrum ◽  
User Authentication ◽  
Characteristic Curve ◽  
Estimation Method ◽  
Frequency Hopping ◽  
Detection Algorithm ◽  
Physical Layer ◽  
Blind Estimation ◽  
Time Frequency

In a frequency hopping spread spectrum (FHSS) network, the hopping pattern plays an important role in user authentication at the physical layer. However, recently, it has been possible to trace the hopping pattern through a blind estimation method for frequency hopping (FH) signals. If the hopping pattern can be reproduced, the attacker can imitate the FH signal and send the fake data to the FHSS system. To prevent this situation, a non-replicable authentication system that targets the physical layer of an FHSS network is required. In this study, a radio frequency fingerprinting-based emitter identification method targeting FH signals was proposed. A signal fingerprint (SF) was extracted and transformed into a spectrogram representing the time–frequency behavior of the SF. This spectrogram was trained on a deep inception network-based classifier, and an ensemble approach utilizing the multimodality of the SFs was applied. A detection algorithm was applied to the output vectors of the ensemble classifier for attacker detection. The results showed that the SF spectrogram can be effectively utilized to identify the emitter with 97% accuracy, and the output vectors of the classifier can be effectively utilized to detect the attacker with an area under the receiver operating characteristic curve of 0.99.

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