About Xing Liu Xing Liu Postdoctoral Research Fellow, Electrical and Computer Engineering attitude determination GNSS localization Postdoctoral researcher in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST) Events Presented Events Apr 30 - May 6, 2023 GNSS Localization and Attitude Determination via Optimization Techniques on Riemannian Manifolds Xing Liu, Postdoctoral Research Fellow, Electrical and Computer Engineering May 3, 16:00 - 18:00 B1 L3 R3119 GNSS localization attitude determination This thesis focuses on Global Navigation Satellite Systems (GNSS)-based localization and attitude determination, essential for navigation and control systems in various platforms. Carrier-phase observations from GNSS signals are more accurate than pseudo-range, but resolving integer ambiguities in carrier-phase data is challenging. The thesis proposes three attitude determination methods based on an optimized GNSS attitude model with nonlinear constraints. Additionally, a joint solution for real-time kinematic positioning and attitude determination is proposed, leveraging the correlation between GNSS data in these two problems. Riemannian optimization is applied to improve the accuracy and ambiguity resolution in both localization and attitude determination.
GNSS Localization and Attitude Determination via Optimization Techniques on Riemannian Manifolds Xing Liu, Postdoctoral Research Fellow, Electrical and Computer Engineering May 3, 16:00 - 18:00 B1 L3 R3119 GNSS localization attitude determination This thesis focuses on Global Navigation Satellite Systems (GNSS)-based localization and attitude determination, essential for navigation and control systems in various platforms. Carrier-phase observations from GNSS signals are more accurate than pseudo-range, but resolving integer ambiguities in carrier-phase data is challenging. The thesis proposes three attitude determination methods based on an optimized GNSS attitude model with nonlinear constraints. Additionally, a joint solution for real-time kinematic positioning and attitude determination is proposed, leveraging the correlation between GNSS data in these two problems. Riemannian optimization is applied to improve the accuracy and ambiguity resolution in both localization and attitude determination.
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