The Integrated navigation numerical correction and prediction of autonomous underwater vehicle (AUV) based on GM (1, 1) model

DOI

10.2991/icismme-15.2015.239How to use a DOI?

Keywords

AUV; integrated navigation; grey mode; Navigation accuracy.

Abstract

Navigation accuracy is one of the crucial performances for autonomous underwater vehicle (AUV), and is an important indicator of evaluating AUV performance. Typically, it is achieving AUV underwater navigation that adopting Doppler velocity log (DVL) integrated Strap down inertia Navigation System (SINS). To improve navigation accuracy of SINS / DVL, this paper embarks from the SINS / DVL integrated navigation model, to sets up filtering state equations and the measurement equation of integrated navigation system, then the grey prediction model GM (1, 1) is added to SINS / DVL integrated navigation system, and the grey prediction algorithm is applied to integrated navigation data analysis. Using the grey prediction model to predicate and correct the navigation data and, further improve the robustness and accuracy of the navigation system. Combined with actual project, the integrated navigation numerical correction and prediction of autonomous underwater vehicle (AUV) based on GM (1, 1) model is proposed. With the relative navigation error as the evaluation index, analyzes the navigation data, calculates relative navigation error of around predication and correction based on GM (1, 1) model; From the result, the introduction of grey prediction model carried on the forecast and the revision to the navigation data may increase the SINS/DVL navigation precision to a certain extent, it explained the accuracy and the usability of the method.

Copyright

© 2015, 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  - Wenbao Geng
AU  - Yu Huang
AU  - Peng Lu
PY  - 2015/07
DA  - 2015/07
TI  - The Integrated navigation numerical correction and prediction of autonomous underwater vehicle (AUV) based on GM (1, 1) model
BT  - Proceedings of the First International Conference on Information Sciences, Machinery, Materials and Energy
PB  - Atlantis Press
SP  - 1126
EP  - 1130
SN  - 1951-6851
UR  - https://doi.org/10.2991/icismme-15.2015.239
DO  - 10.2991/icismme-15.2015.239
ID  - Geng2015/07
ER  -