Rigorous bounding of position error estimates for aircraft surface movement

NextGen will require new navigation and surveillance capabilities to support safe and efficient surface operations based on tightly-coordinated 4D trajectories. In developing these new technologies, such as Automatic Dependent Surveillance-Broadcast (ADS-B) and the Ground Based Augmentation System (GBAS), it is essential to remember that all sensing technologies are prone to rare but potentially hazardous errors. Accordingly, the development of new navigation and surveillance technologies must be complemented by the development of rigorous integrity algorithms that allow pilots and controllers to determine when a sensor system should or should not be trusted. This paper describes the application of a new state-prediction methodology to developing conservative position-error bounds for aircraft ground movement. These position-error bounds can be compared to operational limits in order to generate an alert if the risk of a large navigation error becomes unacceptably high. To demonstrate the conservatism of our approach, we have conducted a series of experiments in a lab setting using a surrogate (robotic) vehicle. These experiments indicate that our method, which we call biased-Gaussian prediction, generates a conservative position-error bound even when more conventional prediction methods do not.