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Tech and academia combine for autonomous research

The research project aims to focus on positioning and timing technologies to improve performance of unmanned vehicles

Project makes use of Spirent's GSS7000 Constellation Simulator, designed for GNSS testing
Project makes use of Spirent's GSS7000 Constellation Simulator, designed for GNSS testing

Spirent Communications, a leading specialist in Galileo, GPS and other global navigation satellite systems (GNSS) testing solutions, has announced a partnership with Cranfield University in the UK to collaborate on connected autonomous vehicle (CAV) technologies.


The aim of the research project is to improve positioning and timing technologies to enable better performance of unmanned vehicles, such as autonomous aircraft or connected cars.


Spirent engineers are working with Cranfield’s postgraduate researchers to develop new methods for synchronisation and location testing, using Spirent’s advanced test systems.


“Creating new ways to verify that autonomous vehicles are in exactly the right place is critical to the development of CAVs,” said Rafal Zbikowski, professor of control engineering at Cranfield University. “Spirent has been verifying GPS/GNSS receivers for 30 years so has a lot of knowledge that will be very useful to our researchers.”


Mark Holbrow, head of engineering at Spirent’s positioning business unit, commented that location awareness for autonomous vehicles is of major importance, and one of the most challenging applications in commercial GNSS development.


“We will be working with Cranfield to create new test and development tools that will provide the opportunity for improved system performance, accuracy and resilience,” he said.


Spirent is supporting a number of individual research projects (IRP) in Cranfield’s Autonomous Vehicle Dynamics and Control (AVDC) MSc programme as an industry partner.


The projects already identified are: GPS-based clock synchronisation for an airborne distributed sensor network and in-car mapping and receiver integration testing for autonomous vehicles.


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