Maximum Mixture Correntropy Criterion-Based Variational Bayesian Adaptive Kalman Filter for INS/UWB/GNSS-RTK Integrated Positioning

Maximum Mixture Correntropy Criterion-Based Variational Bayesian Adaptive Kalman Filter for INS/UWB/GNSS-RTK Integrated Positioning

The safe operation of unmanned ground vehicles (UGVs) demands fundamental and essential requirements for continuous and reliable positioning performance. Traditional coupled navigation systems, combining the global navigation satellite system (GNSS) with an inertial navigation system (INS), provide...

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Bibliographic Details
Main Authors: Sen Wang, Peipei Dai, Tianhe Xu, Wenfeng Nie, Yangzi Cong, Jianping Xing, Fan Gao
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Remote Sensing
Subjects:
maximum mixture correntropy criterion
variational Bayesian
tightly coupled integration
inertial navigation system (INS)/ultra-wideband (UWB)/global navigation satellite system real-time kinematic (GNSS-RTK)
multi-sensor fusion
Online Access:https://www.mdpi.com/2072-4292/17/2/207
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