NSHV trajectory prediction algorithm based on aerodynamic acceleration EMD decomposition

Aiming at the problem of gliding near space hypersonic vehicle (NSHV) trajectory prediction, a trajectory prediction method based on aerodynamic acceleration empirical mode decomposition (EMD) is proposed. The method analyzes the motion characteristics of the skipping gliding NSHV and verifies that the aerodynamic acceleration of the target has a relatively stable rule. On this basis, EMD is used to extract the trend of aerodynamic acceleration into multiple sub-items, and aggregate sub-items with similar attributes. Then, a prior basis function is set according to the aerodynamic acceleration stability rule, and the aggregated data are fitted by the basis function to predict its future state. After that, the prediction data of the aerodynamic acceleration are used to drive the system to predict the target trajectory. Finally, experiments verify the effectiveness of the method. In addition, the distribution of prediction errors in space is discussed, and the reasons are analyzed.

Automated summary

This study proposes a trajectory prediction method based on aerodynamic acceleration empirical mode decomposition, which predicts the future trajectory by analyzing the motion characteristics of the vehicle and the stability rule of aerodynamic acceleration. The effectiveness of the method is verified through experiments, and the distribution of prediction errors in space is discussed, with the reasons analyzed.