Aimed at the problems that the randomness and the inconsistent length of flight motion data are not unanimous, this paper proposes a method of reducing the search space of dynamic time warping (DTW) algorithm and defining the contribution of different feature parameters. Then the flight action can be recognized by multivariate time series fusion of flight data. The preprocessing of the action data is introduced by combining the pre classification and fine classification, then the improved dynamic time warping (WDTW) algorithm is used to identify the measured data. The simulation results show that compared with the traditional DTW algorithm, the WDTW algorithm reduces the complexity of the algorithm, and a change of the computation time is obvious; Finally, according to the analysis of the nuclear density and the precision coefficient, the recognition accuracy is also improved. The accuracy and innovation of the proposed method are valid.