Algorithm for predicting total electron content of global ionized layer

Abstract

The invention provides a global ionized layer electron total content prediction method based on a space-time sequence hybrid framework. According to a prediction method, calculation is made on two types of space-time sequences. For a stabilized spatial sequence, an STARMA model prediction method is constructed. For a non-stationary spatio-temporal sequence, the method comprises the following steps: firstly, extracting a nonlinear space-time trend in a non-stationary space-time sequence by adopting a ConvLSTM method; until the extracted residual error passes the stability test; the calculation efficiency can be greatly improved and the calculation time can be saved by using the parallel calculation method, and meanwhile, the global ionospheric electron content distribution characteristicis fully considered, so that the ionospheric prediction algorithm better conforms to the spatial weather law, and the prediction precision is higher.

Description

technical field [0001] The invention relates to the technical field of ionospheric detection and communication, in particular to an algorithm for predicting the total electron content of the global ionosphere based on a space-time sequence mixed framework. Background technique [0002] With the wide application of global satellite navigation systems in many fields such as surveying and mapping exploration, resource investigation and space atmospheric research, ordinary precision positioning services have been difficult to meet the needs of high-precision users. Among the many factors that affect the positioning accuracy of satellite navigation systems, The positioning error caused by ionospheric delay can reach tens of meters to hundreds of meters, which is an important factor that cannot be ignored in the process of positioning calculation. [0003] The ionosphere is generally the high-altitude atmosphere 60-1000km from the ground, which is partially ionized under the actio...

AI Technical Summary

Problems solved by technology

However, through manual division of grid products, the ionosphere, as a space weather phenomenon, often ignores its own unique spatial distribution characteristics, resulting in the separation of the spatiotemporal characteristics of the electron content during prediction.

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