MIMU/GNSS Tightly-Coupled Covariance Shaping Adaptive Filtering Method for UAV

DOI

10.2991/amcce-17.2017.104How to use a DOI?

Keywords

unmanned aerial vehicle(UAV); adaptive filtering; tightly-coupled; covariance shaping

Abstract

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.

Copyright

© 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/).

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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  -