MT-e&R: NMEA Protocol-Assisted High-Accuracy Navigation Algorithm Based on GNSS Error Estimation Using Multitask Learning

Accurate location data of ground vehicles is very important for various intelligent transportation applications. As one of the most commonly-used navigation solutions at present, the GNSS/INS integrated navigation still cannot meet the accuracy and stability command of current applications. This pap...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2022-11, Vol.23 (11), p.20464-20475
Main Authors: Bao, Linfeng, Luo, Haiyong, Gao, Xile, Ning, Bokun, Zhao, Fang, Zhu, Yida
Format: Article
Language:English
Subjects:
Algorithms
Covariance matrix
Error analysis
Estimation
Global navigation satellite system
GNSS measurement error
GNSS measurement noise covariance matrix
GNSS/INS integrated navigation
Machine learning
Measurement uncertainty
multi-task learning
Navigation
Navigation systems
NMEA protocol
Noise measurement
Position errors
Position measurement
Protocols
Transportation applications
Urban environments
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Accurate location data of ground vehicles is very important for various intelligent transportation applications. As one of the most commonly-used navigation solutions at present, the GNSS/INS integrated navigation still cannot meet the accuracy and stability command of current applications. This paper presents a National Marine Electronics Association (NMEA) protocol data-assisted high-accuracy navigation algorithm based on GNSS position error estimation using multi-task learning (MT-e&R), which can accurately estimate the GNSS position error and GNSS measurement noise covariance matrix with the assistance of protocol data and a multi-task learning model. Extensive experimental results on practical navigation data collected in various urban environments of Beijing demonstrate that our proposed approach can improve the performance of integrated navigation system. The positioning errors of integrated navigation equipped with single-frequency receiver are reduced by 36.17% and 39.58% for double-frequency receiver, which confirms the reasonable environmental adaptability of our proposed MT-e&R algorithm.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2022.3179237