In a new study presented at the IEEE International Conference on Communications in Glasgow, researchers from Queen Mary University of London and partners from around the world showcased the system, called Joint DAS and GNSS (JDG), which blends traditional satellite‑based GPS with a lesser‑known technology referred to as Distributed Acoustic Sensing (DAS).
DAS uses existing fibre‑optic cables—already buried beneath roads and pavements—as ultra‑sensitive vibration sensors. When someone moves nearby, the fibres detect tiny shifts that can be translated into movement patterns.
In a real‑world trial in southern England, the research team logged both GPS data and vibration signals from a roadside fibre‑optic cable as volunteers walked along the route. These combined signals were fed into a deep‑learning model that could continue predicting a person’s location even when GPS was blocked, noisy or only sporadically available.
The collaborators combined expertise from Queen Mary in London, Xi’an Jiaotong University, Xi’an, P.R. China, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India and Chicago State University, Chicago. The results were striking: the JDG system consistently outperformed GPS‑only tracking and other prediction methods, remaining accurate even during complete GPS outages. It also proved resilient on lower‑powered devices that collect fewer location points, suggesting it could support a wide range of smartphones and IoT sensors
The team says the technology could strengthen location services for smart transport, emergency response, and autonomous navigation—particularly in cities and indoor or underground spaces where GPS performance is notoriously unreliable.
10.1109/ICC59461.2026.11587254
An Augmented GNSS-DAS Architecture for Continuous and Robust Positioning
14-Jul-2026