Methods of Compensation of Ionospheric Delay of GNSS Signals: Comparison and Prospects of Application

Global Navigation Satellite Systems (GNSS) are critical for high-precision positioning, navigation, and time synchronization across various domains, including transportation, geodesy, aviation, and scientific research. However, the accuracy of GNSS signals is significantly affected by ionospheric delay, caused by the interaction of radio signals with charged particles in the ionosphere. This delay, influenced by signal frequency, ionospheric conditions, time of day, geographic location, and solar activity, introduces positioning errors that can reach several meters, posing challenges for applications requiring high precision, such as geodesy and autonomous navigation. Existing correction methods, including the widely used Klobuchar model, SBAS augmentation systems, and global ionospheric maps (GIM), have limitations, such as high equipment costs, reliance on external data, or insufficient accuracy in regions with high ionospheric variability. This article reviews current methods for mitigating ionospheric delay, analyzing their features, advantages, and drawbacks, and evaluates their effectiveness in real-time and post-processing coordinate determination tasks. The study highlights that single-frequency GNSS receivers, commonly used in practice, rely on models like Klobuchar, which compensates for approximately 50% of ionospheric errors. More advanced models, such as NTCM and NeQuick, offer improved accuracy, reducing root mean square errors (RMSE) by 0.24–0.45 meters depending on ionospheric conditions. Dual-frequency GNSS receivers, utilizing ionosphere-free linear combinations of L1 and L2 band measurements, provide superior accuracy but require resolving phase ambiguities, which complicates implementation. Regional Total Electron Content (TEC) models outperform global GIMs due to higher spatial-temporal resolution (e.g., 0.5°×0.5° vs. 2.5°×5°), achieving up to 90–95% error reduction in specific cases. Time-series analysis methods, such as ARIMA, SARIMA, and Kalman filtering, enable short-term TEC forecasting, enhancing real-time navigation and geodetic measurements. The article emphasizes the importance of selecting correction methods based on application requirements, receiver type, and regional ionospheric characteristics, advocating for the integration of regional TEC models, dualfrequency measurements, and advanced forecasting techniques to achieve optimal GNSS accuracy