Improved Multi-Sensor Integrated Navigation System for Land-Vehicles

DOI

10.2991/mmeceb-15.2016.40How to use a DOI?

Keywords

extended Kalman filter (EKF), inertia system, integrated navigation system

Abstract

Standalone Beidou satellite navigation system cannot achieve the high positioning accuracy when the signal is obscured. An improved filtering algorithm based on Extended Kalman filter (EKF) is proposed after comparing the advantages and disadvantages of the filtering method. Navigation parameters from SINS and platform error angles are chosen as the state of the system, and navigation parameters from passive-BD are chosen as measurements. The final optimal estimation of navigation parameters including position and speed can be calculated directly. The experimental result indicates that the new algorithm can effectively solve the nonlinearity problem of state equations, and provide continuous positioning result.

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  - Yuyang Zhang
AU  - Bogen Cai
AU  - Jian Wang
PY  - 2015/12
DA  - 2015/12
TI  - Improved Multi-Sensor Integrated Navigation System for Land-Vehicles
BT  - Proceedings of the 2015 2nd International Conference on Machinery, Materials Engineering, Chemical Engineering and Biotechnology
PB  - Atlantis Press
SP  - 200
EP  - 203
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmeceb-15.2016.40
DO  - 10.2991/mmeceb-15.2016.40
ID  - Zhang2015/12
ER  -