Strength in numbers when it comes to inertial sensors

Researchers working in the field of navigation and supported by the Swiss National Science Foundation (SNSF) have developed a method that allows several low-cost inertial sensors working in combination to replace a single expensive sensor.

Inertial sensors such as accelerometers and gyroscopes are used nearly everywhere, from smart watches to submarines, drones, spacecraft, vacuum cleaners and even game controllers. The purpose of these sensors is to indicate the position, speed or direction of an object. Their drawback is their lack of precision, at least when it comes to the low-cost versions used in many devices.

Now there may be a way to solve this problem, with researchers from the University of Geneva reporting that networking several inexpensive sensors is a viable alternative to more powerful sensors. By combining the measurements of several low-cost, individual sensors, the researchers succeeded in obtaining a very precise navigational measurement. Their breakthrough was published in the journal IEEE Transactions on Signal Processing.

“It is as if we had created a virtual sensor, and it is particularly efficient because it uses all the information provided by the individual sensors,” said Yuming Zhang, a PhD candidate in statistics and lead author of the new study. These virtual sensors not only offer the same performance as actual sensors but are also less expensive and can be more flexibly configured. They could therefore be used in a number of consumer devices without increasing their cost.

The idea of combining information from different sensors is not new, but until now technical constraints have limited its application. As explained by Zhang, “Sensor measurement errors are very complex to handle individually, and even more so when several sensors are combined.” The team solved the problem using a new signal decomposition approach, which makes it possible to understand and deal with errors that affect measurements and to process them using a novel statistical method.

According to the researchers, the potential applications of the new technique widely range from aerial mapping using drones to autonomous vehicles. In addition, the ability to optimally combine different sensor technologies could help develop a new generation of global positioning systems.

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