Scientists have found a new, efficient way to crunch GPS data to enhance location accuracy from the meter-level down to a few centimetres.

The optimisation will be used in the development of autonomous vehicles, improved aviation and naval navigation systems and precision technologies, researchers said.

It will also enable users to access centimetre-level accuracy location data through their mobile phones and wearable technologies, without increasing the demand for processing power.

The approach, developed by researchers at University of California, Riverside (UCR), involves reformulating a series of equations that are used to determine a Global Positioning System (GPS) receiver’s position, resulting in reduced computational effort being required to attain centimetre accuracy.

GPS is a space-based navigation system that allows a receiver to compute its location and velocity. Standard GPS yields position measurements accurate to approximately 10 meters.

Differential GPS (DGPS), which enhances the system through a network of fixed, ground-based reference stations, has improved accuracy to about one meter.

However, meter-level accuracy is not sufficient to support emerging technologies like autonomous vehicles, precision farming, and related applications.

"To fulfil both the automation and safety needs of driverless cars, some applications need to know not only which lane a car is in, but also where it is in that lane – and need to know it continuously at high rates and high bandwidth for the duration of the trip," said Jay Farrell, a professor at UCR, who led the study.

This can be achieved by combining GPS measurements with data from an inertial measurement unit (IMU) through an internal navigation system (INS), researchers said.

In the combined system, the GPS provides data to achieve high accuracy, while the IMU provides data to achieve high sample rates and high bandwidth continuously.

Achieving centimetre accuracy requires "GPS carrier phase integer ambiguity resolution." Until now, combining GPS and IMU data to solve for the integers has been computationally expensive, limiting its use in real-world applications.

The UCR team has changed that, developing a new approach that results in highly accurate positioning information with several orders of magnitude fewer computations.

"Achieving this level of accuracy with computational loads that are suitable for real-time applications on low-power processors will not only advance the capabilities of highly specialised navigation systems, like those used in driverless cars and precision agriculture, but it will also improve location services accessed through mobile phones and other personal devices, without increasing their cost," Farrell said.

The study was published in the journal IEEE’s Transactions on Control Systems Technology.

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