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Researchers from California, US, have developed a computationally efficient way to process GPS data in order to improve location accuracy from the metre-level down to a few centimetres.

The research was led by University of California at Riverside’s Bourns College of Engineering professor and chair of electrical and computer engineering Jay Farrell.

The team developed an approach that involves reformulating a series of equations that are used to determine a GPS receiver’s position, leading to less computational effort to improve accuracy.

This optimisation can be used in the development of autonomous vehicles, improved aviation and naval navigation systems, as well as precision technologies.

The technology will enable users to access centimetre-level accuracy location data through their mobile phones and wearable technologies, without a need for an increase of processing power.

GPS is a space-based navigation system, which enables a receiver to compute its location and velocity by measuring the time it takes to receive radio signals from four or more overhead satellites. Due to various error sources, standard GPS yields position measurements accurate to approximately 10m.

Improving the system through a network of fixed, ground-based reference stations, differential GPS (DGPS) has bolstered accuracy to about 1m. However, metre-level accuracy is not enough to support emerging technologies such as autonomous vehicles.

Farrell said: “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.”

According to Farrell, these requirements can be achieved by combining GPS measurements with data from an inertial measurement unit (IMU) through an internal navigation system (INS).

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

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