Skip to main content

Main menu

  • Home
  • Current Issue
  • Archive
  • About Us
    • About NAVIGATION
    • Editorial Board
    • Peer Review Statement
    • Open Access
  • More
    • Email Alerts
    • Info for Authors
    • Info for Subscribers
  • Other Publications
    • ion

User menu

  • My alerts

Search

  • Advanced search
NAVIGATION: Journal of the Institute of Navigation
  • Other Publications
    • ion
  • My alerts
NAVIGATION: Journal of the Institute of Navigation

Advanced Search

  • Home
  • Current Issue
  • Archive
  • About Us
    • About NAVIGATION
    • Editorial Board
    • Peer Review Statement
    • Open Access
  • More
    • Email Alerts
    • Info for Authors
    • Info for Subscribers
  • Follow ion on Twitter
  • Visit ion on Facebook
  • Follow ion on Instagram
  • Visit ion on YouTube
Research ArticleRegular Papers
Open Access

Improving GNSS Positioning Correction Using Deep Reinforcement Learning with an Adaptive Reward Augmentation Method

Jianhao Tang, Zhenni Li, Kexian Hou, Peili Li, Haoli Zhao, Qianming Wang, Ming Liu, and Shengli Xie
NAVIGATION: Journal of the Institute of Navigation December 2024, 71 (4) navi.667; DOI: https://doi.org/10.33012/navi.667
Jianhao Tang
1School of Automation, Guangdong University of Technology, Guangzhou, China
2Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing, Guangzhou, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Zhenni Li
1School of Automation, Guangdong University of Technology, Guangzhou, China
2Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing, Guangzhou, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kexian Hou
1School of Automation, Guangdong University of Technology, Guangzhou, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peili Li
1School of Automation, Guangdong University of Technology, Guangzhou, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Haoli Zhao
2Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing, Guangzhou, China
4School of Artificial Intelligence, Hebei University of Technology, Tianjin, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Qianming Wang
1School of Automation, Guangdong University of Technology, Guangzhou, China
3Techtotop Microelectronics Technology Co., Ltd., Guangzhou, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ming Liu,
5Robotics and Autonomous Systems (ROAS) Thrust, Hong Kong University of Science and Technology, Guangzhou, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Shengli Xie
6Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing, Guangzhou, China
7Guangdong Key Laboratory of Internet of Things Information Technology, Guangzhou 510006, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • References
  • Info & Metrics
  • PDF
Loading

Article Information

vol. 71 no. 4 navi.667
DOI 
https://doi.org/10.33012/navi.667

Published By 
Institute of Navigation
Print ISSN 
0028-1522
Online ISSN 
2161-4296
History 
  • Received October 30, 2023
  • Revision received April 29, 2024
  • Accepted August 3, 2024
  • Published online September 25, 2024.

Copyright & Usage 
© 2024 Institute of Navigation This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Author Information

  1. Jianhao Tang1,2,
  2. Zhenni Li1,2,
  3. Kexian Hou1,
  4. Peili Li1,
  5. Haoli Zhao2,4,
  6. Qianming Wang1,3,
  7. Ming Liu,5 and
  8. Shengli Xie6,7
  1. 1School of Automation, Guangdong University of Technology, Guangzhou, China
  2. 2Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing, Guangzhou, China
  3. 3Techtotop Microelectronics Technology Co., Ltd., Guangzhou, China
  4. 4School of Artificial Intelligence, Hebei University of Technology, Tianjin, China
  5. 5Robotics and Autonomous Systems (ROAS) Thrust, Hong Kong University of Science and Technology, Guangzhou, China
  6. 6Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing, Guangzhou, China
  7. 7Guangdong Key Laboratory of Internet of Things Information Technology, Guangzhou 510006, China
  1. Correspondence
    Zhenni Li, School of Automation, Guangdong University of Technology, Guangzhou 510006, China. Email: lizhenni2012{at}gmail.com
View Full Text

Cited By...

  • 3 Citations
  • Google Scholar
PreviousNext
Back to top

In this issue

NAVIGATION: Journal of the Institute of Navigation: 71 (4)
NAVIGATION: Journal of the Institute of Navigation
Vol. 71, Issue 4
Winter 2024
  • Table of Contents
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on NAVIGATION: Journal of the Institute of Navigation.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Improving GNSS Positioning Correction Using Deep Reinforcement Learning with an Adaptive Reward Augmentation Method
(Your Name) has sent you a message from NAVIGATION: Journal of the Institute of Navigation
(Your Name) thought you would like to see the NAVIGATION: Journal of the Institute of Navigation web site.
Citation Tools
Improving GNSS Positioning Correction Using Deep Reinforcement Learning with an Adaptive Reward Augmentation Method
Jianhao Tang, Zhenni Li, Kexian Hou, Peili Li, Haoli Zhao, Qianming Wang, Ming Liu,, Shengli Xie
NAVIGATION: Journal of the Institute of Navigation Dec 2024, 71 (4) navi.667; DOI: 10.33012/navi.667

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Improving GNSS Positioning Correction Using Deep Reinforcement Learning with an Adaptive Reward Augmentation Method
Jianhao Tang, Zhenni Li, Kexian Hou, Peili Li, Haoli Zhao, Qianming Wang, Ming Liu,, Shengli Xie
NAVIGATION: Journal of the Institute of Navigation Dec 2024, 71 (4) navi.667; DOI: 10.33012/navi.667
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Abstract
    • 1 INTRODUCTION
    • 2 PRELIMINARIES
    • 3 DRL FOR GNSS POSITIONING CORRECTION WITH ARAM
    • 4 EXPERIMENTS
    • 5 CONCLUSION
    • HOW TO CITE THIS ARTICLE
    • ACKNOWLEDGMENTS
    • REFERENCES
  • Figures & Data
  • Supplemental
  • References
  • Info & Metrics
  • PDF

Related Articles

  • Google Scholar

Cited By...

  • No citing articles found.
  • Google Scholar

More in this TOC Section

  • Ranging Performance Evaluation for Higher-Order Scalable Interplex
  • Combinatorial Watermarking Under Limited SCER Adversarial Models
  • Wide-Sense CDF Overbounding for GNSS Integrity
Show more Regular Papers

Similar Articles

Keywords

  • adaptive reward augmentation method
  • deep reinforcement learning
  • global navigation satellite system

Unless otherwise noted, NAVIGATION content is licensed under a Creative Commons CC BY 4.0 License.

© 2025 The Institute of Navigation, Inc.

Powered by HighWire