Classification of aerial missions using Hidden Markov Models

Abstract

This paper describes classification of aerial missions using first-order discrete Hidden Markov Models based on kinematic data. Civil and military aerial missions imply different motion patterns as described by the altitude, speed and direction of the aircraft. The missions are transport, private flying, reconnaissance, protection from intruders in the national airspace as well as on the ground or the sea. A procedure for creating a classification model based on HMMs for this application is discussed. An example is presented showing how the results can be used and interpreted. The analysis indicates that this model can be used for classification of aerial missions, since there are enough differences between the missions and the kinematic data can be seen as observations from unknown elements, or states, that form a specific mission.