Drivers have enjoyed Global Positioning System (GPS) technology for many years now. In addition to cars, GPS is useful in portable electronics or for finding a lost pet or person.
The GPS, however, is not completely suitable for the advent of new autonomous vehicle technology, such as driverless cars or unmanned drones. The main obstacle is the extreme weakness of GPS signals, which make the systems unsuitable in certain environments. Civilian GPS signals also must be unencrypted, making them clear targets of hacking. Finally, GPS signals are prone to jamming and interference.
For these reasons autonomous vehicle technology relies on a set of diverse sensors such as lasers, sonar and cameras in addition to GPS. This approach, however, is too cumbersome and expensive.
To overcome these difficulties a team of researchers at the University of California, Riverside — led by Zak Kassas, assistant professor of electrical and computer engineering at UCR — has developed a highly accurate navigational system that relies entirely on hundreds of available environmental signals, such as radio, TV, Wi-Fi and cellular signals, among others. The system can control an autonomous vehicle either as a standalone system or as a complement of the GPS, making it possible to avoid the use of sensors. Kassas and his team, working at the UCR's Autonomous Systems Perception, Intelligence and Navigation (ASPIN) Laboratory, are testing this concept.
"By adding more and more sensors, researchers are throwing 'everything but the kitchen sink' to prepare autonomous vehicle navigation systems for the inevitable scenario that GPS signals become unavailable. We took a different approach, which is to exploit signals that are already out there in the environment," Kassas said.
In September, the team presented their results at the 2016 Institute of Navigation Global Navigation Satellite System Conference (ION GNSS+), in Portland, Ore., where they demonstrated how to exploit and analyze existing communication signals, called “signals of opportunity (SOP).” They also showed how to build specialized software-defined radios (SDR) that extract SOP timing and position data, how to implement practical navigation algorithms and how to test the system on driverless cars and unmanned drones.
"Autonomous vehicles will inevitably result in a socio-cultural revolution. My team is addressing the challenges associated with realizing practical, cost-effective, and trustworthy autonomous vehicles. Our overarching goal is to get these vehicles to operate with no human-in-the loop for prolonged periods of time, performing missions such as search, rescue, surveillance, mapping, farming, firefighting, package delivery, and transportation," Kassas said.
In addition to Kassas, graduate students Joshua Morales, Joe Khalife, Kimia Shamaei, Jesse Garcia, Sonya Ragothaman and undergraduate student Souradeep (Gogol) Bhattacharya contributed to this research, which was funded with support from the Office of Naval Research (ONR).
A detailed publication by UCR about this article can be found here: UCR Today.