MIMU/GNSS Tightly-Coupled Covariance Shaping Adaptive Filtering Method for UAV
- 10.2991/amcce-17.2017.104How to use a DOI?
- unmanned aerial vehicle(UAV); adaptive filtering; tightly-coupled; covariance shaping
A covariance shaping adaptive Kalman filtering method is newly presented to improve the positioning accuracy of MIMU/GNSS tightly-coupled integrated navigation system for UAV. A dual channel parallel filter scheme with the adaptive filter is proposed to improve the real-time performance and make the tightly-coupled integrated navigation system perform better in complex and dynamic environments. The gain of the covariance shaping adaptive filter is self-tuned by changing covariance weighting factor, which is calculated by minimizing the cost function of the Frobenius norm. Hardware-in-the-loop simulation results indicate that the positioning accuracy of the adaptive Kalman filter is increased by 32.6% against the standard one.
- © 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/).
Cite this article
TY - CONF AU - Bin Liu AU - Rongjun Mu AU - Xin Zhang AU - NaiGang Cui PY - 2017/03 DA - 2017/03 TI - MIMU/GNSS Tightly-Coupled Covariance Shaping Adaptive Filtering Method for UAV BT - Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2017) PB - Atlantis Press SP - 594 EP - 601 SN - 2352-5401 UR - https://doi.org/10.2991/amcce-17.2017.104 DO - 10.2991/amcce-17.2017.104 ID - Liu2017/03 ER -