Uncertainty reduction by an ATS inherent aircraft state vector modelling and estimation

This blog outlines the research activities that are conducted by the Institute of Flight Guidance of the Technische Universitaet Braunschweig, Germany, partly funded by the HALA! Network.

The main objective of this PhD research is to develop a more precise knowledge of an aircraft’s present and future state vector than today. This advanced knowledge will result in an increased predictability of the aircraft’s 4D trajectory, reduced controller workload due to more reliable predictions and an improved performance of the future ATM system in general. The goal is to reduce uncertainty in the trajectory prediction process by taking a more global approach that not only considers aircraft related parameters but also covers external ATS influences. The proposed methodology is to analyse not only straight forward open loop prediction algorithms but to incorporate control strategies that augment the degree of freedom to react to disturbances and therefore render the whole system more predictable.

The focus of this research lies on the incorporation of data that is available on board the aircraft. This internal information used in order to improve knowledge about current and future aircraft states. At the same time, mechanisms are investigated that aim at improving the trajectory tracking itself, such as automatically adapting the trajectory in the short term in order to meet Required Time of Overfly (RTO) constraints.

Within the research suitable trajectory prediction performance criteria are developed that allow a substantiated comparison between different prediction algorithms. As such, definitions known from the performance based navigation will be extended for possible future use in 3D or 4D trajectory operations.

Trajectory deconfliction between flight paths of multiple aircrafts and necessary data links for trajectory data exchange are explicitly not considered in this PHD research. These fields are addressed in other research programs and will be decoupled from the research activities here in order to shift the focus on the aircraft’s 4D trajectory tracking performance.

References
- Eurocontrol, User manual for the Base of Aircraft Data (BADA), Revision 3.9, EEC Report N° 11/03/08-08, Eurocontrol Experimental Centre, Brétigny-sur-Orge, April 2011.
- Vittorio Di Vito et al: Advanced Algorithm for 4D Automatic Navigation. Eurocontrol 9th Innovative workshop, Brétigny, France (2010).
- SESAR Consortium European Air Traffic Management Master Plan 1 Edition 1 (March 30 209)
- Airbus: Getting to Grips with RNP-AP (February 2009).
- ICAO: Performance Based Navigation, Document 9613 (March 30th 2009).
- RTCA inc: ED-75/DO-236B - Minimum Aviation System Performance Standards: Required Navigation Performance for Area Navigation, (October 28th 2003).
- Eurocontrol: Introducing Performance Based Navigation (PBN) and Advanced RNP (A-RNP) (March 8th 2010).