A New Kalman Filtering Method to Resist Motion Model Error In Dynamic Positioning

DOI

10.2991/icmemtc-16.2016.27How to use a DOI?

Keywords

motion model error; adaptive robust kalman filtering; predictive state errors; standardized residuals.

Abstract

Against the disadvantage of traditional kalman filtering which is susceptible to the influence produced by the motion model error, this paper proposes a new kalman filtering method which can resist the motion model error. This new method uses the standardized residuals of the predictive position errors to choose the appropriate least-square principle between two kinds of recursive least-square principles adaptively, so as to achieve the purpose of the robust filtering. The experimental results show that, this new method can effectively weaken the effect of motion model error and track the moving vehicle's trajectory accurately in complex movement environment.

Copyright

© 2016, 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  - Chengsong Zhou
AU  - Jing Peng
AU  - Wenxiang Liu
AU  - Feixue Wang
PY  - 2016/04
DA  - 2016/04
TI  - A New Kalman Filtering Method to Resist Motion Model Error In Dynamic Positioning
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 141
EP  - 146
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.27
DO  - 10.2991/icmemtc-16.2016.27
ID  - Zhou2016/04
ER  -