CORS ionospheric modeling method and device based on linear change characteristics
By capturing the variation characteristics of linear regions of the ionosphere through dynamic order-determined polynomial fitting, the problem of insufficient accuracy in ionospheric modeling in existing technologies is solved, the requirements for station density are reduced, and the positioning accuracy and efficiency of network RTK are improved.
CN121634136BActive Publication Date: 2026-06-23WUHAN UNIV
Patent Information
- Authority / Receiving Office
- CN Β· China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- WUHAN UNIV
- Filing Date
- 2026-02-04
- Publication Date
- 2026-06-23
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Figure CN121634136B_ABST
Abstract
The application discloses a CORS ionosphere modeling method and equipment based on linear variation characteristics, first, a plurality of GNSS stations in linear distribution are selected, observation data is preprocessed and STEC is calculated, and then STEC is projected into VTEC through a single layer model; then, a VTEC dataset along a target direction at the same time is constructed, IPP distance normalization is performed on the ionosphere piercing point, a VTEC reference value is calculated by calling an international reference ionosphere model as a fitting weight, a dynamic order determination strategy is adopted to complete polynomial fitting through a weighted least square method, and a regional ionosphere model is obtained. The VTEC corresponding to a virtual reference station is obtained through interpolation, ionosphere delay is obtained, and the ionosphere delay is further applied in virtual observation value calculation, and linear regional high-precision network RTK calculation is realized. The application fully utilizes the physical characteristics that the ionosphere has variation regularity in the longitude / latitude direction, relaxes the distance requirement between stations, significantly improves the accuracy of the regional ionosphere model, and further improves the observation accuracy of the linear regional network RTK.
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