Proceedings of the 2018 3rd International Conference on Modelling, Simulation and Applied Mathematics (MSAM 2018)

Research on Adaptive UKF Algorithm in Integrated Navigation System

Authors
Jianjun Li, Junshan Li, Jianye Yang
Corresponding Author
Jianjun Li
Available Online July 2018.
DOI
https://doi.org/10.2991/msam-18.2018.38How to use a DOI?
Keywords
component; adaptive estimation principle; Unscented Kalman Filter; integrated navigation
Abstract
According to the characteristics of the combined navigation system and the adaptive UKF filtering algorithm, the navigation accuracy of the integrated navigation system is improved. Firstly, the algorithm of the UKF filtering algorithm is analyzed and the characteristics of the UKF algorithm are summarized, and the adaptive factor is introduced into the UKF filtering algorithm by the adaptive estimation principle, and the improved adaptive UKF algorithm is obtained, and the algorithm is applied to the integrated navigation system. Finally, the simulation calculation of the computer is carried out. The simulation results of adaptive UKF algorithm applied to integrated navigation system are improved, and the results are compared with the results of UKF algorithm. The experimental results show that the improved adaptive UKF can effectively suppress the influence of the initial value selection of the integrated navigation system, reduce the disturbance of the system state model, and effectively improve the precision of the integrated navigation.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Cite this article

TY  - CONF
AU  - Jianjun Li
AU  - Junshan Li
AU  - Jianye Yang
PY  - 2018/07
DA  - 2018/07
TI  - Research on Adaptive UKF Algorithm in Integrated Navigation System
BT  - Proceedings of the 2018 3rd International Conference on Modelling, Simulation and Applied Mathematics (MSAM 2018)
PB  - Atlantis Press
SP  - 179
EP  - 183
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-18.2018.38
DO  - https://doi.org/10.2991/msam-18.2018.38
ID  - Li2018/07
ER  -