ION GNSS+ Session Detail

Session C4: Positioning Technologies and Machine Learning


Date: Thursday, September 19, 2024
Time: 1:45 p.m. - 5:30 p.m.
In-Person presenters in this session provide pre-recorded presentations for viewing by registered attendees on Wednesday, September 18.

Session Chairs

Kinga Wezka
Warsaw University of Technology

Dr. Tara Mina
Stanford University

Track Chair

Dr. Melania Susi
Topcon Positioning System

In-Person Presentations
These presentations will be given in-person at the conference. Presenters will provide a pre-recorded presentation for on-demand viewing by all registered attendees.
1:50 Deep Learning Assisted Kalman Filter for GNSS/MEMS IMU Integration in GNSS Denied Environments
Shuo Li, Bosch, Universität der Bundeswehr München; Thomas Pany, Universität der Bundeswehr München; Maxim Mikhaylov, ETH Zurich; Nikoaly Mikhaylov, Fugro Innovation & Technology
2:12 Artificial Intelligence and Machine Learning for Inertial Measurement Unit Noise Estimation and Denoising
Andrew Isaacson and Garrett Payne, Safran Federal Systems
2:35 AI-Enhanced Smartphone-Based GNSS/INS Integration: Improved Vehicular/Pedestrian Navigation in Challenging Scenarios Using Machine Learning
An-Lin, Tao; Yu-Kai, Lin; Hau-Hsiang, Chan; Li-Min, Lin; Pie-Shan, Kao, Mediatek Inc.
2:58 Improving Smartphone Positioning by Adapting Measurement Noise Covariance using Machine Learning
Anurag Raghuvanshi, Karolina Tchilinguirova, Soroush Sasani, Sunil Bisnath, York University
3:25 - 3:55, Break. Refreshments in Exhibit Hall
4:00 Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Detection and Classification in the Real World
Lucas Heublein, Nisha L. Raichur, Fraunhofer Institute for Integrated Circuits (IIS); Tobias Feigl, Fraunhofer IIS & Friedrich-Alexander-Universität (FAU); Tobias Brieger, Fraunhofer IIS; Fin Heuer, Lennart Asbach, German Aerospace Center (DLR); Jonathan Hansen, Alexander Rügamer, Felix Ott, Fraunhofer IIS)
4:23 GNSS Positioning Uncertainty Estimation in Challenging Environments Using Voting Ensemble Learning
Ni Zhu, Syed Haseeb Ahmad, Valérie Renaudin, AME-GEOLOC, University Gustave Eiffel
4:46 Reinforcement Learning-Based Optimization of GSHARP PPP for Multipath Mitigation in GNSS Positioning
A. Tena, A. Chamorro, E. Carbonell, D. Calle, GMV
5:08 Enhancing Position Estimation with Machine Learning through Postfit Residual Analysis
Alex Lopez-Cruces, Miquel Garcia-Fernandez, Victor Arauzo, Xavier Banqué-Casanovas, Rokubun
Alternate Presentations
Alternate presentations may be given in-person at the conference if other authors are unable to present. Alternate Presenters will provide a pre-recorded presentation for on-demand viewing by all registered attendees.
1. Real Time Feature Detection and Localization Using a Fisheye Camera
Richard Nyquist, Ryan Raettig, Clark Taylor, Scott Nykl, Autonomy and Navigation (ANT) Center
2. Enhanced GNSS Multipath Map in Urban Canyon using User Data Clouding
Yongjun Lee, Byungwoon Park, Sejong University
3. Deep Learning-Based Transition Detection for Seamless Indoor-Outdoor Localization
Chanyeong Ju, Jaeho Jang, Jaehyun Yoo, IPIN LABS
On-Demand Presentations
Pre-recorded presentations will become available for viewing by registered attendees on Wednesday, September 18.
  An ORB-Based SLAM Using Deep Learning for Dynamic Environments
Yiheng Zhao and Hongyang Yu, Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China(UESTC)
  Carrier Phase Availability Classification in Harsh Environment from GNSS Dual-Antenna Low-Cost Receiver Using Machine Learning Models
Rong Yuan, Xiaowei Cui and Mingquan Lu, Department of Electronic Engineering, Tsinghua University; Zhenya Li, Huayuen Technology Co. Ltd; Zhenni Li, School of Automation, Guangdong University of Technology
  Enhancing GNSS Positioning Using Transformer-Based Correction Network
Changyi Zhu, Xidian University; Xueyong Xu, North Information Control Research Academy Group CO., LTD; Yan Na, Xidian University; Cheng Ji, Nanjing University of Science and Technology; Dingcheng Wu, Kefan Wei, North Information Control Research Academy Group CO., LTD
  Performance Analysis of Spoofing Detection Methods Based on Neural Networks
Muhammad Jalal, Chao Sun, Shuai Zhang, Lu Bai, An Wang, ZiChao Qin, Yingzhe He, Beihang University
  Potential Problem Analysis and RF-Based Improvement of RPM on Android Devices
Min He, Hong Li, Hao Wang, and Mingquan Lu, Department of Electronic Engineering, Tsinghua University