For thousands of years people have looked to the sky to navigate their way around the Earth. In the middle of the ocean, with no land in sight, explorers, traders and invaders had only the stars and a compass to keep them on course and guide them to safety.
More recently, of course, we have been looking not to the stars, but to the vast network of satellites that orbit the Earth, continuously transmitting their locations to every smartphone, satnav and receiver that cares to listen. With technology like GPS and other global navigation satellite systems (GNSS), anyone, almost anywhere has instant access to their positional information. These systems are now pivotal to thousands of operations all over the planet, including in the global shipping industry which in 2019 reached a market value of £11 trillion annually.
However, this increasing dependence comes with risk. GPS signals are weak and can be subject to jamming, denial and accidental interference. In 2017, consultancy group London Economics estimated that a GPS disruption to the United Kingdom would have an economic impact of £6.8 bn (adjusted for inflation) over the first five days alone. It is widely suspected that in 2019 the British oil tanker Stena Imperio was drawn into Iranian waters by spoofed (fake) GPS data, and jamming of signals is becoming increasingly common around the Mediterranean, Black and South China seas. Furthermore, GPS signals cannot penetrate the oceans or underground, making them of limited use in submarine exploration and mining operations.
There is demand in the shipping industry therefore, for an alternative way of navigating that is not susceptible to the same vulnerabilities as GNSS. In particular, the current development and deployment of autonomous and semiautonomous cargo vessels designed to reduce shipping costs, increase safety and lower the environmental impact of container shipping requires navigational techniques that are precise enough to enable a vessel to operate entirely independently of an onboard crew. Likewise, under the water, autonomous submarines only have access to GNSS signals at the ocean’s surface, loosing signal as they submerge.
A dependable alternative
Enter inertial sensors. Classical inertial sensors such as accelerometers and gyroscopes have been used for years to measure the changes in acceleration and orientation of an object, and hence track an object’s position over time. These sensors can sit within a ship or a plane and as such are not susceptible to jamming or loss of external signal. The problem – these devices are prone to drifts, and these drifts can add up fast, meaning that very quickly a vessel relying solely on classical inertial sensors will sooner or later have no idea where they are.
Recently, however there has been an explosion of activity in the field of quantum inertial sensors; sensors that, like their classical cousins use acceleration and rotation measurements to track the position of an object without the fragility of GNSS signals but, thanks to exploiting the quirks of quantum mechanics, are able to do so to a much higher accuracy.
How do inertial sensors operate?
While the exact mode of operation of these quantum sensors varies, broadly speaking they rely on cooling a cloud of atoms close to absolute zero. At this temperature the cloud of atoms exhibits quantum coherence, meaning the positions of each atom are correlated with one another. Lasers are used to split the cloud into a quantum superposition, wherein the cloud is directed to head down two different paths at the same time. These two ‘branches’ of the superposition are then caused to recombine, and the resulting quantum interference is measured. Interference is caused by a difference in the lengths of the paths taken by each branch (cloud) of the superposition due to the acceleration and/or rotation of the sensor, and is highly sensitive, allowing precise measurements to be recorded.
These precise measurements mean that the drift of quantum inertial sensors can be much lower than for existing classical sensors.
How is the industry utilising this new technology?
Whilst previously these gains have been confined to textbooks and laboratories, businesses are now beginning to test real-world implementations of the technologies involved in quantum inertial sensors.
One company very aware of the commercial implications are Infleqtion, who in May partnered with BAE Systems and Quinetiq to perform the world’s first flight trials of a quantum-based navigation system in Wiltshire. The project received £8 million in backing from the UK government with the then Science Minister Andrew Griffith, who was abord one of the test flights, eager to highlight the implications of the test “from passenger flights to shipping”. Infleqtion’s Vice President of Strategic Initiatives Max Perez further had to say that “the very first application or very valuable application is going to be autonomous shipping”, a feeling backed up by Infleqtion UK’s recent announcement of plans to test blended quantum and classical sensors at sea with the Royal Navy in early 2025. These hybrid sensors use a continuous quantum sensor output, combined with machine learning, to perform uninterrupted correction of classical inertial sensors, with the effect of improving holdover; the amount of time the sensor can maintain accuracy without external correction, something that currently limits a classical inertial sensor’s ability to operate independently of a GNSS.
In addition to Infleqtion, French technology company Exail, formed from the merger of ECA Group and iXblue, have taken an active interest in this field. They specialise in maritime and navigational technology and have filed several patents for quantum inertial measurement units with this purpose in mind. In 2022 they developed their own hybrid quantum-classical sensor that provides the continuous output of a classical sensor, but with an accuracy 50 times better, addressing the problem of dead-time between measurements in a quantum sensor causing drift.
Other companies are also keen to develop their sensors for the seas. Southampton-based company Aquark technologies, who last year became part of the first cohort of businesses to receive funding from NATO’s innovation accelerator DIANA, recently completed successful trials generating cold atoms on board a Royal Navy vessel. Back in the skies, in May US company AO Sense conducted tests of their 6-axis quantum inertial measurement unit (IMU) on board a Boeing aeroplane. Over the four-hour flight the IMU produced real time navigational data through various operational conditions, further demonstrating the capability of this technology.
Quantum inertial sensors are not the only means by which quantum technology could revolutionise autonomous travel. Quantum gravity meters work in much the same way as quantum accelerometers, but instead of calculating an objects acceleration, they measure the gravitational field strength at the sensor’s location. These devices can be used to produce incredibly precise maps of the Earth’s gravitational field. Armed with these maps and a quantum gravity meter on board, an autonomous marine vehicle such as a submarine could compare the results of their own gravity meter with the data from a gravity map to determine its location under the sea.
It is not just in sensing where quantum technology can help navigation for autonomous vehicles. In order to successfully navigate independently, AVs not only need on-board sensors to aid in self-locating, but also the ability to use this positional information to plot a course. This requires further advances in machine learning capabilities and computing power. Recently, there has been increased interest in using quantum algorithms to address this problem. Quantum computers offer a significant advantage when solving optimisation problems and machine learning problems, and as such could be key to enabling autonomous vehicles to quickly and safely respond to sensor data. For example, Hyundai have been working with IonQ to use quantum computers to process images taken by LIDAR scanners on autonomous cars. Additionally, Indian AI firm QpiAI has filed patents relating to quantum variational algorithms to optimise the positioning of sensors on a vehicle, and quantum software company Classiq has highlighted the potential of a quantum approximate optimisation algorithm to plan logistical operations.
The future of Quantum Tech
It is clear we still have a long way to go before our oceans are navigated by quantum-powered fully autonomous vessels, but the technology required to get there is advancing rapidly, and perhaps it won’t be long until scaled-down quantum inertial sensors are used in tandem with GNSS to provide more a more secure navigational system for manned ships and submarines, representing an important step forward along the path to secure, unjammable navigation.
