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Ionized layer TEC combined prediction method combined with ionized layer chromatography technology

A combined prediction and ionospheric technology, applied in the field of ionospheric detection, can solve problems such as the decline of prediction accuracy, and achieve the effect of time series prediction

Pending Publication Date: 2021-11-02
CIVIL AVIATION UNIV OF CHINA
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Problems solved by technology

However, the above prediction methods all have the phenomenon that the prediction accuracy will decrease with the increase of the prediction time.

Method used

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  • Ionized layer TEC combined prediction method combined with ionized layer chromatography technology
  • Ionized layer TEC combined prediction method combined with ionized layer chromatography technology
  • Ionized layer TEC combined prediction method combined with ionized layer chromatography technology

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Embodiment Construction

[0047] The ionospheric TEC combination prediction method combined with ionospheric chromatography technology provided by the present invention will be described in detail below with reference to the accompanying drawings and specific examples.

[0048] Such as figure 1 As shown, the ionospheric TEC combination prediction method based on the ionospheric tomography technology provided by the invention comprises the following steps carried out in order:

[0049] 1) Based on the GPS observation data, use the ionospheric tomography algorithm to obtain the ionospheric electron density x in the predicted area;

[0050] Specific steps are as follows:

[0051] (a) Using GPS observation data to calculate the tilted total electron content STEC required by the ionospheric tomography algorithm;

[0052] Specific steps are as follows:

[0053] A RINEX file for a GPS receiver contains the following observables:

[0054]

[0055]

[0056]

[0057]

[0058] Among them, P 1 and...

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Abstract

The invention relates to an ionosphere TEC combined prediction method combined with an ionosphere chromatography technology. The method comprises the following steps: calculating the ionized layer electron density of a prediction area by using an ionized layer chromatography algorithm, calculating the total electron content VTEC in the vertical direction, and calculating the VTEC of the prediction area by using an IRI model; constructing a combined prediction model based on the two VTECs, and achieving the model training, model prediction, and model test result and model precision analysis. The invention has the beneficial effects that the LSTM model is used for predicting the chromatography vertical total electron content VTEC, the BP neural network is further used for conducting nonlinear fitting on prediction results of the LSTM model and the IRI model, and therefore the defects of a single prediction model are overcome, and time sequence prediction of the ionospheric vertical total electron content VTEC is better achieved.

Description

technical field [0001] The invention belongs to the technical field of ionospheric detection, in particular to an ionospheric TEC prediction method based on ionospheric tomography technology. Background technique [0002] In systems that use radio signals for high-precision speed measurement, positioning, and other work, the time delay and refraction errors caused by the ionosphere must be eliminated, and these errors are proportional to the total electron content in the ionosphere; using the ionosphere electron content (TEC ) to eliminate the error of the above system is the most accurate, but in the design and requirements of many radio systems, or when the measured value of TEC is missing, a certain ionospheric model must be used to calculate the required ionospheric TEC, and then Errors due to the ionosphere are estimated. [0003] At present, in the study of using empirical models to predict ionospheric TEC, the International Reference Ionosphere IRI (International Ref...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08G01S19/37
CPCG06N3/084G01S19/37G06N3/044G06F18/214
Inventor 尹萍闫晓鹏
Owner CIVIL AVIATION UNIV OF CHINA
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