A new positioning approach unveiled at the IEEE International Conference on Communications in Glasgow blends satellite navigation with a sensing technique usually hidden beneath our feet. Researchers from Queen Mary University of London and international collaborators demonstrated a system called Joint DAS and GNSS (JDG), designed to keep location estimates steady when GPS signals fail or degrade.
At the heart of the method is Distributed Acoustic Sensing (DAS), which turns existing fibre-optic cables into ultra-sensitive vibration detectors. Because fibres react to microscopic strain changes, they can capture signatures produced by footsteps, passing vehicles, or other nearby motion. In other words, the network that already carries data can also “listen” to the physical world.
The study’s real-world trial took place in southern England. Volunteers walked along a roadside route while the team recorded two streams: conventional GPS measurements and vibration data from a buried fibre-optic line. By aligning these modalities, the researchers created a richer view of movement than either signal source could provide alone.
To fuse the information, the team used a deep-learning model trained to translate combined GNSS and DAS observations into continuous location predictions. The key goal was robustness—maintaining tracking performance when GPS becomes noisy, sporadic, or unavailable due to urban canyons, multipath effects, or deliberate jamming.
Results reported by the researchers indicate that JDG consistently outperforms GPS-only tracking and competing prediction strategies. Notably, accuracy remains strong even during complete GPS outages, where traditional systems typically drift or lose lock. This resilience suggests that fibre-based sensing provides a complementary “anchor” to human motion even when satellites cannot.
The architecture also appears practical for deployment on limited hardware. When fewer location points are available—such as on lower-powered devices—the system still performs well, implying that future implementations could scale to a wider range of smartphones and Internet of Things sensors without requiring extensive infrastructure beyond existing fibres.
The team envisions JDG strengthening location services for smart transportation, emergency response, and autonomous navigation. The approach could be particularly valuable in environments where GPS is unreliable, including dense city centres and indoor or underground spaces.
Ultimately, JDG reframes positioning as a multimodal problem: satellites offer broad coverage, while distributed fibre sensors add local, motion-level detail. Together, they form a path toward continuous and dependable navigation in conditions where today’s GNSS-only methods often struggle.
Subject of Research: Continuous and robust positioning using augmented GNSS with Distributed Acoustic Sensing (DAS)
Article Title: An Augmented GNSS-DAS Architecture for Continuous and Robust Positioning
News Publication Date: 14-Jul-2026
Web References: http://dx.doi.org/10.1109/ICC59461.2026.11587254
References: 10.1109/ICC59461.2026.11587254
Image Credits: Not provided
Keywords
Electrical engineering
Tags: deep learning for multi-modal localizationDistributed Acoustic Sensing for location trackingfibre-optic cable vibration detectionGPS signal failure mitigationHybrid positioning systemjoint DAS and GNSS systemmulti-sensor fusion for reliable trackingreal-world fibre-optic sensing trialsresilient navigation technologysatellite navigation and sensing integrationunderground vibration-based sensingurban environment positioning robustness
