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Kriging proxy model algorithm for global ionized layer electron content

A proxy model and electronic content technology, applied in special data processing applications, design optimization/simulation, probabilistic CAD, etc., can solve problems such as long data training cycle, high hardware requirements, poor prediction results, etc.

Active Publication Date: 2020-08-25
BEIHANG UNIV
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Problems solved by technology

The former has better prediction results when the space weather is stable, but it cannot make full use of the historical observation data of the ionospheric electron content, resulting in a waste of data resources. At the same time, it cannot respond when the weather changes drastically, resulting in poor prediction results; the advantages of deep learning methods It can make full use of historical observation data for trend analysis and extraction, but the deep learning method has high requirements for hardware equipment and the data training cycle is long

Method used

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  • Kriging proxy model algorithm for global ionized layer electron content
  • Kriging proxy model algorithm for global ionized layer electron content
  • Kriging proxy model algorithm for global ionized layer electron content

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Embodiment

[0073] This embodiment provides a Kriging proxy model algorithm for establishing global ionospheric electron content based on space weather indices. The algorithm considers ionospheric-related space weather indices to model and predict global ionospheric grid electron content.

[0074] 1. The source of observation data in the model algorithm

[0075] The ionospheric grid electron content data use the global electron content grid products published by the IGS Center such as Figure 2-3 As shown, the currently available ionospheric grid data products have been officially released since 1998. Its products divide the world by 5° difference in longitude and 2.5° difference in latitude, and provide data every hour or two hours. The way to obtain the electron content is to calculate it through a large number of dual-frequency observation data. After years of testing, its accuracy is relatively high and it can reflect the temporal and spatial distribution characteristics of the ionosp...

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Abstract

The invention provides a Kriging proxy model algorithm for global ionized layer electron content. According to the algorithm, long-term stable ionospheric electron content data are obtained by combining a current ionospheric space physical research result with observation of a global satellite navigation system; the Kriging agent model is used for carrying out model construction and ionospheric prediction, the ionospheric prediction precision is improved, meanwhile, a parallel computing method is adopted for carrying out computing according to the characteristic that the global grid data sizeis large, and through the method, many defects of a global ionospheric electron content modeling and prediction method in the prior art are overcome.

Description

technical field [0001] The invention relates to the technical field of ionospheric detection and communication, in particular to a kriging proxy model algorithm for establishing global ionospheric electron content based on space weather index. Background technique [0002] As one of the important components of atmospheric space weather, the ionosphere has an extremely important influence, especially in the field of radio signal transmission, because when electromagnetic wave signals propagate in the ionosphere, they will be affected by the complex electromagnetic environment in the ionosphere, causing their propagation The speed and propagation path change, and the degree of influence of the ionosphere on electromagnetic waves has an extremely important relationship with the degree of ionization of the ionosphere, the electron density in the ionosphere, and the signal frequency of electromagnetic waves. Therefore, with the deepening of radio research, ionosphere research is a...

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Application Information

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IPC IPC(8): G06F30/20G06F111/08
CPCG06F30/20G06F2111/08
Inventor 王志鹏王成薛开宇方堃
Owner BEIHANG UNIV
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