An adaptive cubature Kalman filtering algorithm based on variational mode decomposition for pulsar navigation

Abstract

Aiming at the problem of X-ray pulsar navigation system with uncertain measurement noise, an adaptive cubature Kalman filter (CKF) algorithm is proposed based on variational mode decomposition (VMD). Firstly, the multi-step measurements are predicted by CKF to extend the measurement sequence. Then, the high-frequency noise, which is separated from the extended measurement sequence by VMD, is used to reconstruct the measurement noise. Finally, the measurement noise covariance is estimated based on the reconstructed measurement noise to update the CKF parameters. The simulation results show that the proposed method can adaptively track the change of measurement noise and improve the positioning accuracy of X-ray pulsars navigation system (XPNAV).