Dynamic positioning filter method based on EnKF

DOI

10.2991/iccia-17.2017.164How to use a DOI?

Keywords

Dynamic positioning, nonlinear system state estimation, EnKF, Non-linear observer.

Abstract

In order to improve the positioning accuracy and reliability of the dynamic positioning system and deal with the problem of state estimation of nonlinear system with Gaussian noise, according to the basic principles and methods of Ensemble Kalman Filter (EnKF), a dynamic positioning filtering method is proposed based on EnKF. Then, the simulation results show that the nonlinear observer based on EnKF can effectively estimate the state of the ship and have certain robustness to the observed outliers. The validity of this method is verified at the end of this article.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaogong Lin
AU  - Ruxun Wang
AU  - Dawei Zhao
PY  - 2016/07
DA  - 2016/07
TI  - Dynamic positioning filter method based on EnKF
BT  - Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
PB  - Atlantis Press
SP  - 930
EP  - 938
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-17.2017.164
DO  - 10.2991/iccia-17.2017.164
ID  - Lin2016/07
ER  -