Improved Multi-Sensor Integrated Navigation System for Land-Vehicles
Authors
Yuyang Zhang, Bogen Cai, Jian Wang
Corresponding Author
Yuyang Zhang
Available Online December 2015.
- 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/).
Cite this article
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 -