Adaptive Tracking Algorithm for Hypersonic Maneuvering Target Based on Bi-Satellite Positioning

Due to the hypersonic maneuvering target's fast flight speed and wide trajectory range, it is impractical to track its entire path using ground-based radar. Based on the Bi-satellite positioning measurement model with line of sight intersection, this paper integrate the Strong Tracking Filter (STF) with the Unscented Kalman Filter (UKF) algorithm, incorporating two adaptive coefficients to adjust the filter gain and noise covariance matrix dynamically. This approach aims to track and estimate the trajectory of a hypersonic glide vehicles (HGVs) based on observations from two LEO early warning satellites within the space-based infrared system. Through simulation, this paper presents the results of tracking target trajectories using an adaptive strong tracking Unscented Kalman Filter (ASTUKF) algorithm based on Bi-satellite positioning. The simulation and experimental results demonstrate that the proposed algorithm achieves a 28.95% and 50.36% lower total speed RMSE compared to the other two algorithms, respectively. Similarly, the total position RMSE is reduced by 30.46% and 51.99%, respectively, when compared with the same algorithms.