GNSS underpins many navigation applications, including smartphones and autonomous platforms, but its performance degrades sharply in so-called urban canyons, shaded streets, and other complex outdoor settings. Conventional attempts to compensate often introduce inertial sensors or vision-based systems, which can increase hardware cost, computational load, or sensitivity to lighting and environmental changes. In parallel, commercial 5G networks are expanding worldwide and provide dense base station deployment and wide bandwidth that are attractive for positioning, yet multipath interference, clock bias, and multi-beam transmissions have limited the practical use of 5G signals for robust navigation.

In a study published in Satellite Navigation in 2025, researchers from Wuhan University, The Chinese University of Hong Kong (Shenzhen), and Shandong University of Science and Technology propose a positioning framework that tightly integrates commercial 5G NR signals with GNSS. The framework is designed to enhance navigation reliability in urban settings where satellite signals are often degraded or sparse. By combining advanced 5G tracking techniques with real-time fusion of satellite and cellular measurements, the system delivers more accurate and stable position estimates under practical field conditions.

The team introduces a deep fusion strategy that links improvements in both signal tracking and position estimation. At the signal level, they develop a tracking method that jointly leverages 5G synchronization signals and reference signals to maintain stable lock in multipath-rich environments. This design reduces ranging errors compared with approaches that rely only on basic 5G tracking schemes.

To preserve performance when signals weaken, the researchers incorporate a phase-stabilized Kalman filter into the tracking loop, which helps sustain accurate carrier phase estimates even as signal quality fluctuates. Beyond the front-end tracking enhancements, the study applies an extended Kalman filter to deeply fuse the 5G and GNSS measurements. In contrast to loosely or tightly coupled schemes that leave tracking largely independent, the fused position and clock estimates feed back into the 5G tracking process in real time, correcting it as conditions change.

Field tests in complex outdoor environments demonstrate that this deep integration significantly improves positioning accuracy in both horizontal and vertical dimensions. The integrated system continues to provide reliable positions when satellite visibility is severely limited, conditions under which many GNSS-only solutions fail to maintain acceptable performance. These results indicate that combining 5G and satellite navigation can deliver robust localization under real urban conditions.

"This work shows that commercial 5G signals can do much more than support communication," an author of the study said. "By deeply integrating 5G with GNSS and addressing real-world challenges such as multipath and clock errors, we demonstrate a practical pathway toward reliable urban positioning. The key advantage is robustness - our system continues to work when satellite-only solutions struggle. This opens new possibilities for navigation in cities, where reliable positioning is often the hardest to achieve."

The findings suggest a broad range of potential uses in urban navigation and location-based services. Autonomous vehicles, delivery robots, smart transportation networks, and connected infrastructure could all draw on more dependable positioning in obstructed environments. Because the technique makes use of existing commercial 5G networks, it can be implemented without extensive changes to current infrastructure, supporting future connected systems that require continuous, accurate positioning.

Research Report:5G NR robust tracking and positioning with GNSS assistance

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