Trajectory Sequence Prediction Algorithm for Hypersonic Gliding Target with Variable Maneuver

Abstract

A trajectory prediction algorithm based on ARIMA-UKF is proposed to solve the accuracy problem of trajectory prediction of hypersonic gliding target with variable maneuver in near space. Firstly, the Unscented Kalman Filter (UKF) algorithm is used to track and estimate the state of the target under the condition of target maneuver change, which provides basic data for trajectory prediction. Secondly, the Autoregressive In tegrated Moving Average (ARIMA) model is determined through stationarity analysis, model identification, parameters estimation and model diagnosis of the data, and predicting the acceleration information of the target. Finally, the trajectory of the target is predicted by combining the one-step prediction method in the UKF algorithm. The simulation results show that the UKF algorithm can provide tracking estimation data with position error less than 100 m and velocity error less than 1.2 m/s for trajectory prediction. In the case of target maneuverability, compared with the composite function fitting prediction method, the position accuracy of the ARIMA-UKF algorithm in 150 s, 100 s and 50 s is improved by 5 km, 4.7 km and 2.4 km respectively.

Keywords

• |hypersonic gliding target|trajectory prediction|model identification|arima|ukf