多源数据融合分析平台的构建思路及实践

Construction Ideas and Practice of a Multi-Source Data Fusion Analysis Platform

摘要: 为进一步提升复杂天气下的航空气象服务水平，保障航空运行的安全和顺畅，本文利用多源航空气象数据、航管数据的融合，提出并构建多源数据融合分析平台。该平台实现了多源资料的融合、叠加分析及复杂天气的监视和告警，并从机场和航路点、航线、扇区等多维度监视复杂天气对航空运行的动态影响。案例分析表明，通过多种气象数据与航管数据的融合，不仅能动态监视复杂天气的演变，预估天气影响的时间和范围，还对航路预报准确性进行评估，提升用户使用产品的信心指数。另外，通过实时监视航空器航迹动态变化，掌握复杂天气对飞行中航空器的直接影响，有利于气象、管制人员建立航空器合理规避复杂天气的共同情景意识，从而在决策过程中真正发挥气象数据的支撑作用。

Abstract: To further enhance aviation meteorological services during complex weather and ensure both the safety and efficiency of flight operations, this paper proposes and develops a multi-source data fusion analysis platform by integrating multi-source aviation meteorological data and air traffic management (ATM) data. This platform achieves the fusion and overlay analysis of multi-source data, enables real-time monitoring and alerting for complex weather phenomena, and assesses the impacts of complex weather on aviation operations across multiple dimensions, including airports, way points, routes, and sectors. Case studies demonstrate that integrating meteorological and ATM data not only facilitates dynamic tracking of complex weather evolution and prediction of the spatiotemporal scope of weather impacts, but also evaluates the accuracy in route weather forecasting, thereby increasing user confidence in the products. Furthermore, by monitoring real-time aircraft trajectory deviations, the platform captures the direct impact of complex weather on airborne flights. This enables meteorologists and air traffic controllers to establish a shared situational awareness for rational aircraft avoidance of complex weather, thereby ensuring meteorological data truly supports decision-making processes.