Open AccessAn adaptive cubature Kalman filtering algorithm based on variational mode decomposition for pulsar navigation
Author(s) -
Yang Jiahui,
Gao Shesheng,
Li Guo,
Gao Zhaohui
Publication year - 2022
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/cmu2.12453
Subject(s) - kalman filter , noise (video) , algorithm , computer science , covariance , pulsar , navigation system , mode (computer interface) , noise measurement , mathematics , noise reduction , artificial intelligence , physics , statistics , astrophysics , image (mathematics) , operating system
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).