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Short-term ionosphere forecasting method and device based on NARX

A technology for ionospheric forecasting and forecasting values, applied in the field of global navigation satellite system satellite positioning, can solve problems such as insufficient TEC forecasting accuracy, and achieve the effect of improving positioning accuracy and forecasting accuracy

Active Publication Date: 2020-04-21
SOUTHEAST UNIV
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Problems solved by technology

[0005] Purpose of the invention: Aiming at the problem of insufficient short-term ionospheric TEC prediction accuracy, a short-term ionospheric prediction method and device based on NARX is proposed, and a TEC prediction model is established, which can effectively improve the ionospheric TEC prediction accuracy

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Embodiment Construction

[0034] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0035] Such as figure 1 As shown, the embodiment of the present invention discloses a short-term ionospheric forecasting method based on NARX, which mainly includes the following steps:

[0036] Step 1) Download historical TEC data files from the IGS FTP server to obtain TEC grid data for 120 consecutive days. The data file is called GIM, and it is obtained by unified calculation of the observation values ​​of about 200 base stations distributed around the world by IGS and other organizations.

[0037] Step 2) According to the latitude and longitude of the observation station, the single-point TEC time series of 120 consecutive days is obtained by bilinear interpolation, expressed as:

[0038]

[0039] In the formula, TEC(φ,λ) represents the TEC at latitude φ and longitude λ, and TEC(φ i ,λ i ), (i=0,1) represent the TEC values ​​at the ...

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Abstract

The invention discloses a short-term ionosphere forecasting method and device based on NARX. The method comprises the steps that: TEC grid data in a continuous period of time are obtained from a historical TEC data file; then, according to the longitude and latitude of an observation station, a single-point TEC time sequence in the period of time is obtained in a bilinear interpolation mode; an NARX neural network model is established, the NARX model is trained by using the TEC time sequence, wherein input parameters comprise the TEC time sequence and a time sequence of external time parameters, and output is a TEC prediction value of the next moment; and finally, real-time prediction is carried out according to the trained NARX model to obtain a TEC prediction value at a future moment. With the method provided by the invention, the prediction precision of the TEC of the ionosphere can be improved, and the positioning precision can be improved when the method is applied to GNSS positioning.

Description

technical field [0001] The present invention relates to a global navigation satellite system (Global Navigation Satellite System, GNSS) satellite positioning method, in particular to a short-term ionospheric forecast method and device based on a nonlinear autoregressive neural network (Nonlinear Autoregressive with Exogenous input, NARX) with external input. Background technique [0002] The ionosphere is an important part of the near-Earth space, distributed within the range of 60-1000km from the Earth's surface. Due to the influence of solar radiation and various cosmic rays, the atmospheric molecules in this part are ionized to produce a large number of free electrons. The distribution of free electrons in the atmosphere is very complex and disordered, causing electromagnetic wave signals passing through it to cause varying degrees of interference, including refraction, scattering, reflection, and absorption. Since the formation of the ionosphere is the joint action of s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S19/37G06F30/20G06N3/04G06N3/08
CPCG01S19/37G06N3/049G06N3/08G06N3/045
Inventor 潘树国张正协高成发高旺喻国荣赵涛
Owner SOUTHEAST UNIV
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