Trains currently rely on expensive trackside equipment for positioning because satellite navigation fails in tunnels and rural areas. This project builds a hybrid sensor that combines a quantum accelerometer—using ultra-cold atoms to measure motion with extreme precision—with a classical accelerometer that can take fast readings. Neither works well alone: quantum sensors drift slowly but are accurate over time, while classical sensors are fast but accumulate errors. By fusing them into a single unit, the team aims to deliver long-term positioning accuracy at least ten times better than current classical systems, while maintaining high-frequency measurements. The sensor will be designed for 3D printing, reducing size, weight, and cost to make it commercially viable. If successful, the technology could replace expensive trackside infrastructure on the rail network, enabling cheaper, more reliable train control in tunnels and remote areas. The project will test the hybrid sensor on a moving vehicle to demonstrate its real-world performance.
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Quantum sensing technologies offer levels of measurement precision, accuracy, and stability that exceed those offered by classical (or non-quantum) approaches. An area where this performance enhancement shows great potential is in positioning, navigation and timing (PNT) systems. An important subcategory of PNT systems are ones based on inertial navigation systems. These calculate a relative position from a known starting point based on continuous measurements of acceleration, rotation, and time. Such systems are essential in environments where satellite navigation systems are either unavailable, such as when underground or underwater, or when they are actively denied. Precise positioning is a safety-critical component of the rail network, which currently relies on expensive trackside infrastructure and onboard equipment rather than satellites which can be unreliable in tunnels and rural areas. Future network upgrades will require new reliable and affordable PNT technologies beyond the capabilities of classical devices alone. Currently, the long-term positioning accuracy of such systems is severely limited by the performance of the classical acceleration sensors that they use, even in state-of-the-art incarnations. The performance of acceleration sensors based on atom interferometry with ultra-cold atoms offer at least an order of magnitude improvement on the long-term positioning accuracy of such classical inertial navigation systems. Despite this potential, quantum sensors cannot compete with the high frequency measurements of classical sensors. By combining quantum and classical acceleration sensors within a single unit to form a hybrid device, we can get the best of both worlds - high frequency measurements and long-term accuracy. There are currently no commercially available products that deliver the benefits of cold atom acceleration sensing. Harnessing the power of additive manufacturing (AM), commonly referred to as 3D printing, our project will enable the delivery of an economical hybrid sensor with components suitable for mass production. Using designs optimised for AM, complex structures not possible with conventional techniques can be engineered to reduce the size, weight, and costs of the devices without sacrificing performance, making them more commercially attractive to customers. Our project will make significant progress towards demonstration of commercial viability through performance evaluations of our hybrid acceleration sensor on a moving vehicle.
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