Adaptive data fusion for air traffic control surveillance

This paper describes a method to enhance current surveillance systems used in air traffic control. Those systems are currently based on statistical data fusion, relying on a set of statistical models and assumptions. The proposed method allows for the on-line calibration of those models and enhanced detection of non-ideal situations, increasing surveillance products integrity. It is based on the definition of a set of observables from the fusion process and a rule based expert system with the objective to change processing order, algorithms or even remove some sensor data from the processing chain.