稻城圆环阵太阳射电成像望远镜系统实时成像快视处理架构

Radio telescopes play a vital role in radio astronomical observations by detecting and analyzing celestial radio emissions, including their intensity, spectrum, and polarization. In recent years, advancements in observational technology have significantly improved the resolution and sensitivity of radio telescopes. As a result, these systems have become increasingly large and complex, accompanied by a rapid growth in scientific data volume. The imaging fast view subsystem is primarily responsible for real-time system status monitoring and fault diagnosis of large telescope arrays. Its real-time processing efficiency is critical to ensuring the overall operational performance and stability of the telescope system. Addressing the real-time fast view requirements of large-scale interferometric arrays—efficiently processing massive amounts of observational data, reducing data processing latency, and ensuring real-time responsiveness—is a key challenge that constrains the effectiveness of fault diagnosis and the long-term operational reliability of large radio telescope systems. It remains an urgent issue in the development of large-scale radio astronomy arrays. Daocheng Radio Telescope, currently the world’s largest synthetic aperture radio imaging telescope, enables real-time monitoring of solar radio flares and continuous tracking of the formation, evolution, and interplanetary propagation of coronal mass ejections. This capability is of great importance for advancing research on Sun-Earth interactions and analyzing the impact of solar activity on Earth. To support continuous and automated monitoring of its operational status and real-time fault diagnosis, this paper presents the design and implementation of a complete and efficient imaging fast-view automation framework. The framework focuses on three aspects: fast view data parsing, data storage, and data visualization. It optimizes existing data parsing procedures, improves the storage structure for complex data, and ultimately achieves real-time imaging fast-view capabilities for massive telescope data. This provides crucial support for stable system operation and automated fault analysis. The framework has been validated in actual observation tasks of the Daocheng Radio Telescope. Experimental results show that it reduces the overall processing time for imaging fast-view tasks to 14.3% of the original duration, significantly enhancing the speed and responsiveness of the system, and greatly improving the telescope’s real-time observation and fault diagnosis capabilities. Moreover, this framework offers theoretical and practical reference for other telescope projects, supporting national strategic scientific needs and promoting high-level scientific research. Its successful application not only strengthens China’s international competitiveness in radio astronomy but also provides robust technical support for real-time fault diagnosis in future large-scale astronomical observation projects.