Dr. Diana Fontanella
AirBus Defence and Space
Dr. Naser El-Sheimy
University of Calgary
Deborah Lawrence
Federal Aviation Administration
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. |
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1:50 | Effectiveness of Neural Network Approaches for the Acquisition of Non-Periodic Spreading Codes : Marco Trombini, Davide Leone, Angelo Bruno, Marco D’Addezio, Gianluca Falco, Emanuela Falletti, Leonardo S.p.A. | ||||
2:12 | Evaluation of (Un-)Supervised Machine-Learning-Based Detection, Classification, and Localization Methods of GNSS Interference in the Real World : Tobias Feigl, Fraunhofer Institute for Integrated Circuits (IIS), & Friedrich-Alexander-Universität (FAU); Tobias Brieger, Felix Ott, Fraunhofer IIS, & Ludwig-Maximilians-Universität (LMU); Jonathan Hansen, David Contreras Franco, Alexander Rügamer, Wolfgang Felber, Fraunhofer IIS | ||||
2:35 | Ionosphere VTEC Map Forecasting Based on Graph Neural Network with Transformers : Ruirui Liu, Yiping Jiang, Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University | ||||
2:58 | A Deep Learning Approach for a Real-Time Ionospheric Delay Forecasting Map System : Andre L.A. Silva - Instituto Tecnológico de Aeronáutica; Moises S. Freitas - Instituto Tecnológico de Aeronáutica; Clodoaldo Faria Jr - Universidade Estadual Paulista; Paulo R.P. Silva - Instituto Tecnológico de Aeronáutica; Alison O. Moraes - Instituto de Aeronáutica e Espaço; Bruno C. Vani - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo; Jonas Sousasantos - The University of Texas at Dallas; João F.G. Monico - Universidade Estadual Paulista; | ||||
3:25 - 3:55, Break. Refreshments in Exhibit Hall | |||||
4:00 | Transformer Deep Learning for Real-Time Precise Orbit Corrections : Wahyudin P. Syam, Shishir Priyadarshi, Andrés Abelardo García Roqué, Alejandro Pérez Conesa, GMV; Guillaume Buscarlet, Mickael Dall’Orso, European Space Agency (ESA) | ||||
4:23 | Deep Learning in GNSS Orbit and Clock Extended Predictions to Improve the Accuracy and Robustness of Positioning : Li-Hsiang Chu, Yin-Lien Lo, Yao-cheng Lin, Shi-Xian Yang, AIROHA Technology (Company of MediaTek Group) | ||||
4:46 | Tightly Coupled Graph Neural Network and Kalman Filter for Improving Smartphone GNSS Positioning : Adyasha Mohanty and Grace Gao, Stanford University | ||||
5:08 | First Real-World Results of a Deep Neural Network Assisted GNSS/INS Kalman-Filter with MEMS Inertial Sensors for Autonomous Vehicle : Shuo Li, Robert Bosch GmbH and Bundeswehr University Munich; Maxim Mikhaylov, ITMO University; Nikolay Mikhaylov, Robert Bosch GmbH; Thomas Pany, Mohamed Bochkati, Bundeswehr University Munich | ||||
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. | High-Solar Activity Ionospheric Modelling Using Machine Learning: A Comparison Against Classical Models : Shishir Priyadarshi, Wahyudin P. Syam, Andrés Abelardo García Roqué, Alejandro Pérez Conesa, GMV; Guillaume Buscarlet, Raül Orús Pérez, Mickael Dall’Orso, European Space Agency (ESA) | ||||
2. | Assessing Machine Learning Approach for GNSS Satellite Orbit Prediction : Kannan Selvan, Akpojoto Siemuri, Fabricio S. Prol, Petri Välisuo, Heidi Kuusniemi, University of Vaasa | ||||
3. | Inter-System Bias Estimation Using the MAFA Method : Dawid Kwasniak, Slawomir Cellmer, The University of Warmia And Mazury in Olsztyn | ||||
4. | GSSC Now: Data-Centric Digital Platform to Boost Exploitation of GNSS Science Opportunities : Vicente Navarro, ESA; Sara del Rio, Luis Mendes, Jordi Prados, Emilio Fraile, RHEA for ESA; Maria del Mar Millán, Alain Messina, Miguel Barragán, Marcos Castro, GMV; Javier Ventura-Traveset, ESA |
Virtual Presentations ![]() Pre-recorded presentations will become available for viewing by registered attendees on Wednesday, September 13. | |||||
A Machine Learning-based Approach for Correcting Cooperative DGNSS Differential Corrections : Guoqiang Zeng, Hongbo Zhao, Chen Zhuang, Shan Hu, Beihang University | |||||
A Robust RF Fingerprint Extraction Scheme for GNSS Spoofing Detection : Chengjun Guo, University of Electronic Science and Technology of China (UESTC), China; Zhongpei Yang, University of Electronic Science and Technology of China (UESTC) | |||||
Efficient Graph Neural Network driven Reinforcement Learning for GNSS Position Correction : Zhenni Li, Zhuoyu Wu, Haoli Zhao, School of Automation, Guangdong University of Technology; Shengli Xie, Guangdong Key Laboratory of IoT Information Technology; Qianming Wang, Techtotop Microelectronics Technology Co. Ltd. | |||||
Incremental Learning for LOS/NLOS Classification of Global Navigation Satellite System : Yuan Sun, Shang Li, Zhongliang Deng, School of Electronics Engineering, Beijing University of Posts and Telecommunications |
For Attendees Technical Program Registration Hotel Travel and Visas Conference Committee Exhibits Submit Kepler Nomination For Authors and Chairs Abstract Management Author Resource Center Session Chair Resources Panel Moderator Resources Student Paper Awards Editorial Review Policies Publication Ethics Policies For Exhibitors Exhibitor Resource Center Marketing Resources Other Years Future Meetings Past Meetings