In view of the current problems such as insufficient accuracy of ionospheric real-time and forecast data and the difficulty in fusing multi-source heterogeneous data, this paper designs a set of ionospheric fusion processing and forecasting system based on Global Navigation Satellite System (GNSS) and vertical observation data, aiming to provide high-precision and high-timeliness ionospheric environment information services for radio system applications. This system adopts Limited Kalman Filter Model, based on the Kylin operating system and cloud computing platform. It utilizes container cloud, high availability, and distributed architecture to achieve high-precision real-time and forecast reports of the total electron content (TEC), critical frequency of the F2 layer (foF2), and electron density in the global and surrounding areas of China. Experimental tests show that the system has a current reporting delay of approximately 5 minutes and a spatial-temporal resolution of 5°×2.5°×15 min, representing a significant improvement over traditional data processing methods. Additionally, the system supports three-dimensional electron density visualization, providing reliable data support for applications such as ionospheric research, satellite navigation correction, shortwave communication, and ground-based radar. It offers high-precision and high-timeliness ionospheric environment information services for radio system applications.