Global and Local Consistency Methodology for Ionospheric dSTEC Interpolation | IEEE Journals & Magazine | IEEE Xplore

Global and Local Consistency Methodology for Ionospheric dSTEC Interpolation

Publisher: IEEE

Abstract:

The accuracy of ionospheric delay modeling for user stations is intimately tied to the precise characterization of the ionospheric information in the domain of Global Nav...View more

Abstract:

The accuracy of ionospheric delay modeling for user stations is intimately tied to the precise characterization of the ionospheric information in the domain of Global Navigation Satellite Systems (GNSSs). Current methods for model identification often face difficulties due to the scarcity of data from limited and sparsely located ground reference stations, and the irregular ionospheric characteristics during active periods. This is particularly true in active low latitudes, where disturbances, including GNSS signal scintillation and influence outcomes. This article introduces a universal framework, termed the global and local consistency methodology (GLCM), dedicated to extracting ionospheric spatial information by aligning estimated characteristics across global and subset spatial information. The proposed model adheres to a specifically designed objective to generate the appropriate form of functions and, based on them, to derive the ionospheric information for given areas. We carried out the simulation test to intuitively demonstrate the capabilities to improve the accuracy of the model in a direct and noninterference way. In addition, the model has been verified based on real-world data at low latitudes from a network of ground GNSS stations from all visible Global Position System (GPS) and GALILEO (GAL) satellites. The model achieves a reduction in the root-mean-square error (RMSE) of differential slant total electron content (dSTEC) by approximately 18% and 15% compared with the multiquadratic model and the Kriging model, respectively, during periods of high ionospheric activity. The proposed model has demonstrated effectiveness in ionospheric modeling and is actively being adapted for a wide range of GNSS applications and beyond.
Article Sequence Number: 5801816
Date of Publication: 21 August 2024

ISSN Information:

Publisher: IEEE

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