@article{ZHANG2022, 
author = {Lifei ZHANG and Shaoping WANG and Maria Sergeevna SELEZNEVA and Konstantin Avenirovich NEUSYPIN},
title = {A new adaptive Kalman filter for navigation systems of carrier-based aircraft},
year = {2022},
journal = {Chinese Journal of Aeronautics},
volume = {35},
number = {1},
pages = {416-425},
keywords = {Adaptive filters, Apriori statistics, Deck landing aircraft, Innovation sequence, State noise covariance},
url = {https://www.sciopen.com/article/10.1016/j.cja.2021.04.014},
doi = {10.1016/j.cja.2021.04.014},
abstract = {The features of carrier-based aircraft’s navigation systems during the approach and landing phases are investigated. A new adaptive Kalman filter with unknown state noise statistics is proposed to improve the accuracy of the INS/GNSS integrated navigation system. The adaptive filtering algorithm aims to estimate and adapt the unknown state noise covariance Q in high dynamic conditions, when the measurement noise covariance R is assumed to be known empirically in advance. The new adaptive Kalman filter based on the innovation sequence and pseudo-measurement vector approach makes it more effective to estimate and adapt Q. The simulation results and semi-physical experiments show that the application of the proposed adaptive Kalman filter can guarantee a higher estimation accuracy of the state variables.}
}