一种面向电离层电子密度的多卫星系统间误差校正方法
By using the COSMIC-2 satellite as a benchmark, combined with a dual BP neural network and an adaptive spatiotemporal weight allocation method, the ionospheric electron density data of the FY-3 satellite was corrected, which solved the problem of inconsistent data quality among multiple satellite systems and improved the accuracy of the ionospheric model and the accuracy of satellite navigation and positioning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- KUNMING UNIV OF SCI & TECH
- Filing Date
- 2025-08-13
- Publication Date
- 2026-07-17
AI Technical Summary
The quality of ionospheric electron density data varies among different satellite systems. Existing methods struggle to achieve stable and accurate error compensation and data correction under complex spatial distributions, affecting the accuracy of ionospheric models and satellite navigation and positioning.
Using the ionospheric electron density of the COSMIC-2 satellite as a benchmark, the ionospheric electron density data of the FY-3 satellite is corrected through a dual BP neural network and an adaptive spatiotemporal weight allocation method. Combined with the residual dispersion parameter MAD and physical constraint boundaries, error correction between multiple satellite systems is achieved.
It improves the prediction accuracy of the ionospheric electron density model based on multi-source data fusion, enhances the accuracy and reliability of satellite navigation and positioning, and meets the reliability standards for global navigation and positioning error tolerance and space weather early warning.
Smart Images
Figure CN121028144B_ABST