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Towards an integrity monitoring for 4D-trajectories

For the years 2030 and beyond aircraft are expected to fly optimal trajectories that are defined in the form of three dimensional waypoints plus associated required times of overfly. In order to maintain separation and exploit the benefits of these 4D-trajectories, aircraft must stay within very small volumes around the reference track. Challenging uncertainties arise when it comes to unpredictable events like for example fast changes of meteorological conditions. Some of those imperfections during the prediction phase of the trajectory can be later compensated by closed loop control. Therefore, this work introduces the notion of uncertainty prior and after closed loop control. That approach splits the predicted trajectory tracking performance into traditional aircraft performance and other input parameter prediction, together with their associated uncertainty sources and another block that models the capability of controls to soften the impact of certain input variations. This aims at determining what input uncertainties could be compensated by applying closed loop or manual control and finally to come up with a more reliable aircraft state prediction not only in terms of accuracy but also with respect to integrity. In order to do so, uncertainties on the relevant input factors must be identified. Their impact on the state estimate has to be quantified in scenarios with and without closed loop control. The paper will present an approach towards a quantification of the predicted state variable, exemplarily for the Estimated Time of Arrival (ETA) prediction. The outcome is a prerequisite for specifying accuracy and integrity of the predicted future aircraft states that will provide benefit to a more reliable trajectory tracking in the context of future Air Traffic Systems. It will further discuss the remaining gaps between the integrity monitoring of today's aircraft trajectory tracking compared to fully 4D contained trajectory operation as it is envisaged by the SESAR master plan [1].