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The ionosphere plays a critical role in radio wave propagation, impacting satellite-based communication and navigation systems. This study evaluates near-real-time ionosphere maps (NRTIMs) derived from dual-frequency Global Positioning System (GPS) observations and validates them against established ionosphere models. Using dual-frequency Global Navigation Satellite System (GNSS) technology, the research mitigates ionospheric errors by measuring phase delays at L1 and L2 frequencies. Global ionosphere maps (GIMs) generated by the International GNSS Service (IGS) provide essential ionospheric corrections. Our approach combines accurate GPS observations with regional modeling to enhance GNSS positioning accuracy. The results demonstrate the effectiveness of the developed MATLAB algorithm in estimating ionospheric delays, showing strong convergence with GIMs. The results show a significant convergence between the Regional Ionosphere Modeling of RIM, IGS (Final Ionosphere Product), IGU (Ultra Rapid Ionosphere Product), and IGR (Rapid Ionosphere Product), as the highest average values during the 77th DOY of winter 2020 at the CPVG station were 14.753 TECU for RIM and 14.736, 14.7373 and 14.731 TECU at the CPVG station for IGS, IGU, and IGR while the average was for RIM, IGS, IGU, and IGR are respectively lower, with the lowest average values during the 190th DOY of autumn 2020 at station IZMI with a value of 3.5472 TECU for RIM, 3.5541, 3.5421 and 3.5624 TECU at IZMI station for IGS, IGU, and IGR respectively. By achieving strong agreement with existing GIMs and providing high-frequency results, the algorithm improves the reliability of GPS systems by effectively monitoring envelope disturbances. Ionic and dilute.
The ionosphere plays a critical role in radio wave propagation, impacting satellite-based communication and navigation systems. This study evaluates near-real-time ionosphere maps (NRTIMs) derived from dual-frequency Global Positioning System (GPS) observations and validates them against established ionosphere models. Using dual-frequency Global Navigation Satellite System (GNSS) technology, the research mitigates ionospheric errors by measuring phase delays at L1 and L2 frequencies. Global ionosphere maps (GIMs) generated by the International GNSS Service (IGS) provide essential ionospheric corrections. Our approach combines accurate GPS observations with regional modeling to enhance GNSS positioning accuracy. The results demonstrate the effectiveness of the developed MATLAB algorithm in estimating ionospheric delays, showing strong convergence with GIMs. The results show a significant convergence between the Regional Ionosphere Modeling of RIM, IGS (Final Ionosphere Product), IGU (Ultra Rapid Ionosphere Product), and IGR (Rapid Ionosphere Product), as the highest average values during the 77th DOY of winter 2020 at the CPVG station were 14.753 TECU for RIM and 14.736, 14.7373 and 14.731 TECU at the CPVG station for IGS, IGU, and IGR while the average was for RIM, IGS, IGU, and IGR are respectively lower, with the lowest average values during the 190th DOY of autumn 2020 at station IZMI with a value of 3.5472 TECU for RIM, 3.5541, 3.5421 and 3.5624 TECU at IZMI station for IGS, IGU, and IGR respectively. By achieving strong agreement with existing GIMs and providing high-frequency results, the algorithm improves the reliability of GPS systems by effectively monitoring envelope disturbances. Ionic and dilute.
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