Maximum Correntropy Criterion-based UKF for Tightly Coupling INS and UWB with non-Gaussian Uncertainty Noise

Seong Cho, Jae Lee, Chan Park

2022

Abstract

In this paper, unscented Kalman filter (UKF) based on maximum correntropy criterion (MCC) instead of minimum mean square error (MMSE) criterion, and it is applied to tightly coupled integration of inertial navigation system (INS) and ultra wide-band (UWB). UWB can measure distance with an accuracy of less than 30cm in line-of-sight environment, but provides distance measurement with various types of non-Gaussian uncertainty noise in non-line-of-sight environment. In this case, if the INS/UWB system is configured with the existing MMSE-based filter, a large error occurs. To solve this problem, in this paper, UKF is designed based on MCC. Through simulation analysis, it is confirmed that the proposed filter has robust characteristics against UWB uncertainty and enables stable INS/UWB integration.

Paper Citation

in Harvard Style

Cho S., Lee J. and Park C. (2022). Maximum Correntropy Criterion-based UKF for Tightly Coupling INS and UWB with non-Gaussian Uncertainty Noise. In Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-585-2, pages 209-213. DOI: 10.5220/0011286000003271

in Bibtex Style

@conference{icinco22,
author={Seong Cho and Jae Lee and Chan Park},
title={Maximum Correntropy Criterion-based UKF for Tightly Coupling INS and UWB with non-Gaussian Uncertainty Noise},
booktitle={Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2022},
pages={209-213},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011286000003271},
isbn={978-989-758-585-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Maximum Correntropy Criterion-based UKF for Tightly Coupling INS and UWB with non-Gaussian Uncertainty Noise
SN - 978-989-758-585-2
AU - Cho S.
AU - Lee J.
AU - Park C.
PY - 2022
SP - 209
EP - 213
DO - 10.5220/0011286000003271