Abstract: Military aircraft flight action have strong randomness and ambiguity. In order to realize the recognition and division of military aircraft flight action, a Markov Random Field (MRF) based recognition and division algorithm is proposed. The flight data segment is divided and clustered to realize the recognition and division of flight actions. Simulation experiments show that, compared with traditional flight action  recognition algorithms, the flight action recognition algorithm based on the MRF model has a higher recognition rate.

Key words: Markov random field, action recognition, multivariate time series, clustering