scholarly journals Fiber-optic time-frequency transfer in gigabit ethernet networks over urban fiber links

2021 ◽  
Vol 29 (8) ◽  
pp. 11693
Author(s):  
Zhan Lu ◽  
Youzhen Gui ◽  
Jialiang Wang ◽  
Kang Ying ◽  
Yanguang Sun ◽  
...  
Keyword(s):  
Fiber Optic ◽  
Gigabit Ethernet ◽  
Time Frequency ◽  
Ethernet Networks ◽  
Frequency Transfer ◽  
Fiber Links

scholarly journals Modeling and Performance Evaluation of Precise Positioning and Time-Frequency Transfer with Galileo Five-Frequency Observations

2021 ◽  
Vol 13 (15) ◽  
pp. 2972
Author(s):  
Wei Xu ◽  
Wen-Bin Shen ◽  
Cheng-Hui Cai ◽  
Li-Hong Li ◽  
Lei Wang ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Satellite Orbit ◽  
Average Frequency ◽  
Satellite System ◽  
Observation Data ◽  
Navigation Satellite ◽  
Dual Frequency ◽  
Time Frequency ◽  
Combination Model ◽  
Frequency Transfer

The present Global Navigation Satellite System (GNSS) can provide at least double-frequency observations, and especially the Galileo Navigation Satellite System (Galileo) can provide five-frequency observations for all constellation satellites. In this contribution, precision point positioning (PPP) models with Galileo E1, E5a, E5b, E5 and E6 frequency observations are established, including a dual-frequency (DF) ionospheric-free (IF) combination model, triple-frequency (TF) IF combination model, quad-frequency (QF) IF combination model, four five-frequency (FF) IF com-bination models and an FF uncombined (UC) model. The observation data of five stations for seven days are selected from the multi-GNSS experiment (MGEX) network, forming four time-frequency links ranging from 454.6 km to 5991.2 km. The positioning and time-frequency transfer performances of Galileo multi-frequency PPP are compared and evaluated using GBM (which denotes precise satellite orbit and clock bias products provided by Geo Forschung Zentrum (GFZ)), WUM (which denotes precise satellite orbit and clock bias products provided by Wuhan University (WHU)) and GRG (which denotes precise satellite orbit and clock bias products provided by the Centre National d’Etudes Spatiales (CNES)) precise products. The results show that the performances of the DF, TF, QF and FF PPP models are basically the same, the frequency stabilities of most links can reach sub10−16 level at 120,000 s, and the average three-dimensional (3D) root mean square (RMS) of position and average frequency stability (120,000 s) can reach 1.82 cm and 1.18 × 10−15, respectively. The differences of 3D RMS among all models are within 0.17 cm, and the differences in frequency stabilities (in 120,000 s) among all models are within 0.08 × 10−15. Using the GRG precise product, the solution performance is slightly better than that of the GBM or WUM precise product, the average 3D RMS values obtained using the WUM and GRG precise products are 1.85 cm and 1.77 cm, respectively, and the average frequency stabilities at 120,000 s can reach 1.13 × 10−15 and 1.06 × 10−15, respectively.

SmartARP: merging IP and MAC addressing for low-cost gigabit Ethernet networks

1999 ◽  
Vol 31 (21) ◽  
pp. 2193-2204 ◽  
Author(s):  
Andris Sidorovs ◽  
Guntis Barzdins ◽  
Janis Lacis ◽  
Karlis Ogsts
Keyword(s):  
Low Cost ◽  
Gigabit Ethernet ◽  
Ethernet Networks

scholarly journals A research on fiber-optic vibration pattern recognition based on time-frequency characteristics

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881346 ◽  
Author(s):  
Tabi Fouda Bernard Marie ◽  
Dezhi Han ◽  
Bowen An ◽  
Jingyun Li
Keyword(s):  
Pattern Recognition ◽  
Frequency Domain ◽  
Time Domain ◽  
Fiber Optic ◽  
Pattern Recognition Method ◽  
Recognition Method ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Vibration Pattern ◽  
The Time Domain

To detect and recognize any type of events over the perimeter security system, this article proposes a fiber-optic vibration pattern recognition method based on the combination of time-domain features and time-frequency domain features. The performance parameters (event recognition, event location, and event classification) are very important and describe the validity of this article. The pattern recognition method is precisely based on the empirical mode decomposition of time-frequency entropy and center-of-gravity frequency. It implements the function of identifying and classifying the event (intrusions or non-intrusion) over the perimeter to secure. To achieve this method, the first-level prejudgment is performed according to the time-domain features of the vibration signal, and the second-level prediction is carried out through time-frequency analysis. The time-frequency distribution of the signal is obtained by empirical mode decomposition and Hilbert transform and then the time-frequency entropy and center-of-gravity frequency are used to form the time-frequency domain features, that is, combined with the time-domain features to form feature vectors. Multiple types of probabilistic neural networks are identified to determine whether there are intrusions and the intrusion types. The experimental results demonstrate that the proposed method is effective and reliable in identifying and classifying the type of event.

scholarly journals Key technology of high-precision time frequency transfer via 200 km desert urban fiber link

2019 ◽  
Vol 68 (6) ◽  
pp. 060602
Author(s):  
Kang Ying ◽  
You-Zhen Gui ◽  
Yan-Guang Sun ◽  
Nan Cheng ◽  
Xiao-Feng Xiong ◽  
...  
Keyword(s):  
High Precision ◽  
Key Technology ◽  
Time Frequency ◽  
Precision Time ◽  
Fiber Link ◽  
Frequency Transfer

Optical Two-Way Time-Frequency Transfer across a Three-Node Free-Space Network

2020 ◽  
Author(s):  
Martha I. Bodine ◽  
Jennifer L. Ellis ◽  
William C. Swann ◽  
Sarah A. Stevenson ◽  
Jean-Daniel Deschenes ◽  
...  
Keyword(s):  
Free Space ◽  
Time Frequency ◽  
Space Network ◽  
Frequency Transfer
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