GNSS localization

Abdulkarem Badiea Alshaibani

MS Student at the Information Science Lab at the King Abdullah University of Science and Technology (KAUST).

GNSS Localization and Attitude Determination via Optimization Techniques on Riemannian Manifolds

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B1 L3 R3119

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.

Xing Liu

Postdoctoral Research Fellow, Electrical and Computer Engineering
Postdoctoral researcher in Electrical and Computer Engineering at King Abdullah University of Science and Technology (KAUST)