GAO, Yixin (The Hong Kong Polytechnic University), Wen, Weisong (Hong Kong Polytechnic University), LIU, Xikun (The Hong Kong Polytechnic University), Huang, Feng (The Hong Kong Polytechnic University), Hu, jiahao (The Hong Kong Polytechnic University), Su, Dongzhe (Hong Kong Applied Science and Technology Research Institute (AST)

Enhancing LEO-GNSS Positioning in Urban Canyons: A Factor Graph Optimization Approach with StarLink Simulations

Scheduled for presentation during the Regular Session "S13b-Localization, Mapping, and Sensing for Robust Navigation in ITS" (WE-EA-T13), Wednesday, November 19, 2025, 14:10−14:30, Stradbroke

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 19, 2025

Abstract

Extensive research has explored augmenting GNSS positioning with LEO satellites to enhance urban accuracy and reliability. However, effectively integrating LEO and GNSS constellations remains an open challenge. To address this, this paper proposes a scalable, open-source Factor Graph Optimization (FGO) framework for LEO-GNSS positioning, designed to seamlessly integrate additional sensors. By jointly optimizing pseudorange and Doppler shift measurements from both constellations, the framework aims to improve positioning accuracy and stability. Validation using complex urban canyon datasets from Hong Kong and simulated Starlink signals demonstrates notable accuracy improvements over GNSS-only systems. Furthermore, this study releases the first open-source FGO-based LEO-GNSS fusion positioning algorithm, providing a foundational platform for autonomous systems research.