Detection of aircraft divergence from its flight plan in the vertical plane

A methodology and algorithms for the detection of divergences of aircraft from their flight plans on the vertical plane are presented. Deviations from the flight plan are often the result of human error, such as miscommunication between the pilot and the air traffic controller (ATC), situational awareness errors of the ATC, discrepancies between the mental picture of the ATC and his/her decision support tools, etc. The goal is to detect divergences due to these factors as early as possible and provide a timely warning. The difficulty is distinguishing these "important" divergences from generic deviations, due for example to local wind conditions. Here we develop algorithms for addressing this problem, inspired by methods from fault detection and isolation. The algorithms are tested on a simulation of a Boeing 767-300 flying in a wind field with realistic spatio-temporal correlation structure.