Parameter Blind Estimation of Frequency-Hopping Signal Based on Time–Frequency Diagram Modification

2017 ◽  
Vol 97 (3) ◽  
pp. 3979-3992 ◽  
Author(s):  
Weihong Fu ◽  
Xiaohui Li ◽  
Naian Liu ◽  
Yongqiang Hei ◽  
Juan Wei
Keyword(s):  
Frequency Hopping ◽  
Blind Estimation ◽  
Time Frequency ◽  
Frequency Diagram

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.

Research on Frequency Hopping Parameters of Hybrid Spread Spectrum Signal

2014 ◽  
Vol 543-547 ◽  
pp. 2551-2554
Author(s):  
Gang Fu ◽  
Dong Xu Zhu ◽  
Yue Feng
Keyword(s):  
High Resolution ◽  
Frequency Analysis ◽  
Spread Spectrum ◽  
Frequency Hopping ◽  
Frequency Parameter ◽  
Frequency Signal ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Aerospace Monitoring ◽  
Frequency Diagram

In recent decades, Hybrid Spread Spectrum (DS/FH) signals has been rapidly developed and extensively used in the field of both military communications and aerospace monitoring. Through the study of hybrid spread spectrum signal, firstly use time-frequency analysis to get the time-frequency diagram of hybrid spread spectrum signal, and then wipe off the DS pseudo-code, lastly use the high-resolution frequency to estimate the parameters of hopping frequency signal, in order to provide a kind of ideas and reference to test hopping frequency parameter of hybrid spread spectrum signal.

scholarly journals Study on the Relationship between Electrical Tree Development and Partial Discharge of XLPE Cables

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Chaofei Gao ◽  
Yanlong Yu ◽  
Zan Wang ◽  
Wei Wang ◽  
Liwei Zheng ◽  
...  
Keyword(s):  
Statistical Characteristics ◽  
Time Frequency ◽  
Experimental Platform ◽  
Equivalent Time ◽  
Electrical Tree ◽  
Electrical Trees ◽  
Insulation Breakdown ◽  
The Relationship ◽  
Frequency Diagram ◽  
Tree Development

Based on the slice materials of 35 kV and 110 kV XLPE cables, an experimental platform is built to study the relationship between electrical tree and PDs in XLPE with different voltage levels. There are three significant statistical characteristics of the PDs during the growth of electrical trees. The analysis of the results shows that each growth stage has certain characteristics. Different features existed between the growth of the electrical trees and the PD in the insulation of the 35 and 110 kV cables. Evident characteristics such as large spans of time and frequency were present as the electrical trees grew violently in the equivalent time-frequency diagram at every stage. These results could provide criteria for the identification of the deterioration using PD to monitor cables in service at rated voltages. The results are important for the identification of defects in cable insulation in order to provide an early warning of insulation breakdown in the cables.

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