scholarly journals A Study on the Diffraction Correction Prediction of Electromagnetic Field Intensity Based on the Method of Estimating Aerial Access Network Signal

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jialuan He ◽  
Zirui Xing ◽  
Qiang Wang ◽  
Feihong Wu ◽  
Fuyong Lu

Field strength is a typical indicator of air access network signals, and the prediction of field strength has important reference significance for the estimation of aerial access network signals. However, many factors affecting the field strength, such as path, terrain, sunshine, and climate, increase the computational complexity, which greatly increases the difficulty of establishing an accurate prediction system. After persistent research by researchers in recent years, the ITU-R P.1546 model has gradually become a point-to-surface forecasting method for ground services recommended by ITU for ground operations in the frequency range of 30 MHz~3000 MHz. In view of the characteristics of electromagnetic signal propagation in mountainous environment, the influence of diffraction is also considered in this paper. Based on more accurate scene information such as actual terrain, the prediction calculation of electromagnetic signal propagation in a mountainous environment is proposed by using the corrected ITU-R P.1546 model. In addition, the influence of the actual terrain is taken into account to correct the relevant parameters, and the predicted results are compared with the measured data. The results indicate that field strength prediction results of the ITU-R P.1546 model based on the diffraction effect correction proposed in this paper in specific physical areas have better performance than those of the traditional ITU-R P.1546 model. Among them, the determination coefficient between the measured data and the predicted results is 0.87, the average error is 5.097 dBμV/m, and the root mean square error is 6.6228 dBμV/m, which proves that the ITU-R P.1546 model based on the corrected model is effective in the prediction of electromagnetic field intensity in the actual mountainous environment.

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1216
Author(s):  
Xin Wang ◽  
Bo Li ◽  
Fan Zhao ◽  
Xinyu Luo ◽  
Luxi Huang ◽  
...  

Due to the occlusion of the moon, an annular solar eclipse will have an effect on the ionosphere above the earth. The change of the ionosphere, for the low-frequency time-code signal that relies on it as a reflection medium for long-distance propagation, the signal field strength, and other parameters will also produce corresponding changes, which will affect the normal operation of the low-frequency time-code time service system. This paper selects the solar eclipse that occurred in China on 21 June 2020, and uses the existing measurement equipment to carry out experimental research on the low-frequency time-code signal. We measured and analyzed the signal field strength from 20 June 2020 to 23 June 2020, and combined solar activity data, ionospheric data, and geomagnetic data, and attempted to explore the reasons and rules of the change of signal parameters. The results showed that the field strength of the low-frequency time-code signal changed dramatically within a short time period, the max growth value can reach up to 17 dBμV/m and the variation trend yielded ‘three mutations’. This change in signal field strength is probably due to the occurrence of a solar eclipse that has an effect on the ionosphere. When the signal propagation conditions change, the signal strength will also change accordingly.


2000 ◽  
Vol 78 (1) ◽  
pp. 21-27 ◽  
Author(s):  
C. Harris ◽  
W. Boivin ◽  
S. Boyd ◽  
J. Coletta ◽  
L. Kerr ◽  
...  

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 3131-3138 ◽  
Author(s):  
Bernard B. Munyazikwiye ◽  
Hamid Reza Karimi ◽  
Kjell G. Robbersmyr

2012 ◽  
Vol 12 (3&4) ◽  
pp. 231-252
Author(s):  
Luis Octavio Castanos

We consider two two-level atoms fixed at different positions, driven by a resonant monochromatic laser field, and interacting collectively with the quantum electromagnetic field. A Born-Markov-secular master equation is used to describe the dynamics of the two atoms and the steady-state is obtained analytically for a configuration of the atoms. The steady-state populations of the energy levels of the free atoms, entanglement, quantum and geometric discords and degree of mixedness are calculated analytically as a function of the laser field intensity and the distance between the two atoms. It is found that there is a possibility of considerable steady-state entanglement and left/right quantum discord and that these can be controlled either by increasing/decreasing the intensity of the laser field or by increasing/decreasing the distance between atoms. It is shown that the system of two atoms can be prepared in a separable mixed state with non-zero quantum discord that turns into an $X$-state for high laser field intensities. The behavior and relationships between the different correlations are studied and several limiting cases are investigated.


2020 ◽  
Vol 61 (2) ◽  
pp. 25-34 ◽  
Author(s):  
Yibo Li ◽  
Hang Li ◽  
Xiaonan Guo

In order to improve the accuracy of rice transplanter model parameters, an online parameter identification algorithm for the rice transplanter model based on improved particle swarm optimization (IPSO) algorithm and extended Kalman filter (EKF) algorithm was proposed. The dynamic model of the rice transplanter was established to determine the model parameters of the rice transplanter. Aiming at the problem that the noise matrices in EKF algorithm were difficult to select and affected the best filtering effect, the proposed algorithm used the IPSO algorithm to optimize the noise matrices of the EKF algorithm in offline state. According to the actual vehicle tests, the IPSO-EKF was used to identify the cornering stiffness of the front and rear tires online, and the identified cornering stiffness value was substituted into the model to calculate the output data and was compared with the measured data. The simulation results showed that the accuracy of parameter identification for the rice transplanter model based on the IPSO-EKF algorithm was improved, and established an accurate rice transplanter model.


2014 ◽  
Vol 962-965 ◽  
pp. 564-569 ◽  
Author(s):  
Yan Chao Shao ◽  
Liang Jun Xu ◽  
Yan Zhu Hu ◽  
Xin Bo Ai

Pressure monitoring is an important means to reflect the running status of the natural gas desulphurization process. By using the data mining technology, the interaction relationships between the pressure and other monitoring parameters are analyzed in this paper. A pressure trend prediction model is established to show the pressure status in the natural gas desulfurization process. Firstly, the theory of Principal Component Analysis (PCA) is used to reduce the dimensions of measured data from traditional Supervisory Control and Data Acquisition (SCADA) system. Secondly the principal components are taken as input data into the pressure trend prediction model based on multiple regression theory of Support Vector Regression (SVR). Finally the accuracy and the generalization ability of the model are tested by the measured data obtained from SCADA system. Compared with other prediction models, pressure trend prediction model based on PCA and SVR gets smaller MSE and higher correlation. The pressure trend prediction model gets better generalization ability and stronger robustness, and is an effective complement to SCADA system in the natural gas desulphurization process.


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