Improve decision-making process in Air Command and Control Systems with meteorological data fusion

The decision-making process can be complex in critical environments because it is associated with uncertain conditions. Air operations, in particular, require an effective decision-making process to guarantee safety and efficiency, where in addition, external factors such as weather conditions re-strict operations or generate adverse effects on human lives, infrastructure, economic resources, and equipment. Therefore, this work introduces a computerized decision aid methodology, implementing data fusion for aircraft location, and detecting me-teorological phenomena to identify possible interactions between these two entities. For this, detecting meteorological phenomena uses satellite images, allowing the identification of dangerous meteorological phenomena for aviation, such as convective clouds and lightning. On the other hand, the fusion of data sources allows aircraft detection, location, and tracking. The resulting information is integrated into the Colombian Air Force's operational command and control system to support decision-making, helping to improve safety standards, with algorithms and methodologies based on operational experience, and aimed at the automatic identification of risks for air operation.