Wi-Fi, LTE ambient signals to replace, augment GPS

Signals of Opportunity (SOP), such as Wi-Fi, TV and LTE cellular radio signals, could provide stronger and more secure location services than satellite GPS

Wi-Fi, LTE ambient signals to replace, augment GPS
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Future self-driving cars and up-and-coming commercial drone aviation are behind a mad scramble to find a better solution for location services than the satellite Global Positioning System (GPS).

Advances in Signals of Opportunity (SOP), along with software-defined radios, could be the solution.

GPS isn’t ideal. Firstly, it’s a free service made available by the U.S. government out of the kindness of its heart, and the civilian element could conceivably be switched off in times of national crisis—there are no contracts with smartphone makers, for example.

Secondly, GPS wasn’t really designed for non-military applications such as civilian automobile navigation—it’s a weak signal and prone to interference, including that from space weather. It’s also not secure at the civilian level. It’s completely unencrypted and open to spoofing, in fact. Further, GPS jamming could bring existing satellite-based systems to a standstill.

A 2012 Homeland Security report released late last year under the Freedom of Information Act painted a gloomy future for civilian GPS. Communications companies aren’t prepared to protect GPS systems, which they, banking, IT verticals, and others use for timekeeping, the government said then.

The best alternative to GPS

The best alternative to GPS is tapping “into the hundreds of signals around us at any point in time, like LTE, cellular, radio, television, Wi-Fi and other satellite signals,” and analyzing them, say University of California, Riverside (UCR) researchers in an article on their website, "No GPS, No Problem: Next-Generation Navigation."

The article announces two papers on the subject. One is specifically related to LTE positioning (pdf), and the other is about more broad-based SOP radio-aided navigation (pdf).

Environmental signals, coupled with algorithms, should be “used as a standalone alternative to GPS or [to] complement current GPS-based systems,” the scientists say.

That would “enable highly reliable, consistent and tamper-proof navigation”—something GPS and its competitors, such as Russian system GLONASS, the European system Galileo, and a Chinese system called Beidou, haven’t been able to provide. 

Augmenting GPS for autonomous vehicles

The UCR-proposed SOP system goes one step beyond how many autonomy developers intend to augment GPS for autonomous vehicles.

Developers are aware of GPS’ shortcomings, and many intend to use Inertial Navigation Systems (INS) and more to augment it.

INS essentially adds a collection of sensors to GPS. The sensors second-guess where the vehicle has travelled. Accelerometers and gyroscopes use dead-reckoning to figure a position, for example. Barometers can figure altitude, which when combined with speed and distance, can give some insight as to the location. “Cameras, lasers and sonar” can also be incorporated, the university researchers explain.

That team, however, wants to also use collected radio data, the signals of opportunity, and says that by doing so, autonomy will be more accurate and reliable. Algorithms analyze radio signals around the vehicle. The scientists will likely add their system to a combination of GPS and INS.

The military is also going that route, even though its GPS is often encrypted in that environment. BAE Systems is working on an SOP system called NAVSOP.

We want 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,” says Zak Kassas, assistant professor of electrical and computer engineering in UCR’s Bourns College of Engineering, in the article.

It’s an “inevitable scenario that GPS signals become unavailable” at some point, he says.

Tapping into radio signals around us, along with INS sensor data, could contribute to a realization of “practical, cost-effective and trustworthy autonomous vehicles.”

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