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Session E3a: All-Source Intelligent PNT Methods


Date: Thursday, September 14, 2023
Time: 8:30 a.m. - 10:05 a.m.
Location: Capitol Ballroom 1-3 (Fourth Floor)
In-Person presenters in this session provide pre-recorded presentations for viewing by registered attendees on Wednesday, September 13.

Session Chairs

Dr. Guohao Zhang
The Hong Kong Polytechnic University

Dr. Ryan Watson
Xona Space Systems

Track Chair

Dr. Li-Ta Hsu

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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 virtual attendees.
8:35 Improvements to GNSS Positioning in Challenging Environments by 3DMA Lidar Informed Selective Satellites Usage
Russell Gilabert, Julian Gutierrez, Evan Dill, NASA Langley Research Center Best Presentation
8:57 Seamless Navigation for Indoor-Outdoor Positioning Using GNSS-Aided UWB/WiFi/IMU System
Akpojoto Siemuri, Mahmoud Elsanhoury, Kannan Selvan, Petri Välisuo, Heidi Kuusniemi, Mohammed S. Elmusrati, University of Vaasa
9:20 A Hybrid Deep Learning Approach for Robust Multi-Sensor GNSS/INS/VO Fusion in Urban Canyons
Patrick Geragersian, School of Aerospace, Transport and Manufacturing (SATM), Cranfield University; Ivan Petrunin, Weisi Guo, Centre for Autonomous and Cyberphysical Systems, Cranfield University; Raphael Grech, Technical Strategist in Emerging Technologies, Spirent Communications PLC
9:43 Defining an Integrity Metric for Diverse, Multi-Sensor PNT Devices

John Fischer, Safran Navigation and Timing
10:05-10:35, Break. Refreshments in Exhibit Hall
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 virtual attendees.
1. Android GNSS/INS Using Complementary Filter
Dong-Kyeong Lee, Evan Gattis, Dennis Akos University of Colorado Boulder; Jeonghyeon Yun, Byungwoon Park, Sejong University Peer Reviewed
2. Exploring the Benefits of Deep Learning-Based Sensors Error Estimation for Improved Attitude and Position Accuracy
Eslam Mounier, Queen's University, and Ain Shams University; Paulo Ricardo Marques de Araujo, Queen's University; Mohamed Elhabiby, Micro Engineering Tech Inc.; Michael Korenberg, Queen's University; Aboelmagd Noureldin, Royal Military College, and Queen's University Peer Reviewed