GPS Tracking Down to the Centimeter

GPS Tracking Down to the Centimeter

Technology developed at UCR will be used for high precision positioning in mobile devices, autonomous vehicles and related applications


a photo of a smartwatch with map guide


The new technology will enable users to access centimeter-level accuracy location data through their mobile phones and wearable technologies, without increasing the demand for processing power.

RIVERSIDE, Calif. ( — Researchers at the University of California, Riverside have developed a new, more computationally efficient way to process data from the Global Positioning System (GPS), to enhance location accuracy from the meter-level down to a few centimeters.

The optimization will be used in the development of autonomous vehicles, improved aviation and naval navigation systems, and precision technologies. It will also enable users to access centimeter-level accuracy location data through their mobile phones and wearable technologies, without increasing the demand for processing power.

The research, led by Jay Farrell, professor and chair of electrical and computer engineering in UCR’s Bourns College of Engineering, was published recently in IEEE’s Transactions on Control Systems Technology. The approach involves reformulating a series of equations that are used to determine a GPS receiver’s position, resulting in reduced computational effort being required to attain centimeter accuracy.

First conceptualized in the early 1960s, GPS is a space-based navigation system that allows 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 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. But meter-level accuracy isn’t sufficient to support emerging technologies like autonomous vehicles, precision farming, and related applications.

“To fulfill 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 Farrell, whose research focuses on developing advanced navigation and control methods for autonomous vehicles.

Farrell said 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 high bandwidth continuously.

Achieving centimeter 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 specialized 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 research was done by Farrell, Yiming Chen, and Sheng Zhao. Chen and Zhao received their Ph.D.s at UCR. Chen now works for Qualcomm. Zhao now works for Google.

The UCR Office of Technology Commercialization has filed patents for the inventions above.

February 13, 2016 / by / in , , , , , ,

Leave a Reply

Show Buttons
Hide Buttons

IMPORTANT MESSAGE: is a website owned and operated by Scooblr, Inc. By accessing this website and any pages thereof, you agree to be bound by the Terms of Use and Privacy Policy, as amended from time to time. Scooblr, Inc. does not verify or assure that information provided by any company offering services is accurate or complete or that the valuation is appropriate. Neither Scooblr nor any of its directors, officers, employees, representatives, affiliates or agents shall have any liability whatsoever arising, for any error or incompleteness of fact or opinion in, or lack of care in the preparation or publication, of the materials posted on this website. Scooblr does not give advice, provide analysis or recommendations regarding any offering, service posted on the website. The information on this website does not constitute an offer of, or the solicitation of an offer to buy or subscribe for, any services to any person in any jurisdiction to whom or in which such offer or solicitation is unlawful.