Global ionospheric total electron content prediction system
US10852439B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 16, 2020 |
| Grant date | Dec 1, 2020 |
| Priority date | — |
| Expiry date | Jul 16, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention provides a global ionospheric total electron content prediction system based on a spatio-temporal sequence hybrid framework. The prediction system implements computational processing for two types of spatio-temporal sequences, wherein for a stationary spatio-temporal sequence, a STARMA model prediction method is constructed in the present invention; for a non-stationary spatio-temporal sequence, a nonlinear spatio-temporal trend is firstly extracted from the non-stationary spatio-temporal sequence by adopting a ConvLSTM method until the extracted residual passes a stationarity test, and then the electron content is predicted using the STARMA model prediction method. By using a parallel computing method in the present invention, the computational efficiency can be greatly improved, and the operation time can be saved; meanwhile, the global ionospheric electron content distribution characteristics are fully considered, so that the ionospheric prediction algorithm itself is more in line with the space weather law and has a higher prediction accuracy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.