- New navigation system relies on Earth’s magnetic field
- Contract seeks to address issues with satellite signals
By Katrina Manson (Bloomberg) -- The US Air Force is preparing to test quantum navigation as an alternative to GPS signals with help from startup SandboxAQ, according to the company.
The Google spinoff, which is due to announce Monday that it won a $1.2 million Small Business Innovation Research contract with the Air Force, will develop a prototype for a new navigation system that relies on the Earth’s magnetic field, rather than on satellite signals that can be jammed, spoofed or otherwise degraded, according to Jen Sovada, president of the public sector for SandboxAQ.
Reports of GPS jamming in Ukraine, Norway and Russia from officials, analysts and pilots have increased since Russia’s invasion of Ukraine last year, accelerating Pentagon concerns that the US needs fail-safe alternatives.
As part of the initial deal, the US Air Force will flight-test quantum navigation aboard C-17 cargo planes, which transport people, food and fuel and provide critical logistical support during conflict, according to the company and US Air Force Major Kyle McAlpin.
“We should have backups to GPS,” McAlpin told Bloomberg News. McAlpin, who is also a pilot, is a project liaison at the Air Force’s artificial intelligence accelerator hosted at the Massachusetts Institute of Technology. The accelerator is working to develop magnetic navigation with SandboxAQ. GPS, short for Global Positioning System, is operated and maintained by the US Space Force and is a space-based, radio-navigation system with 31 satellites.
SandboxAQ’s concept relies on quantum sensors that detect the earth’s magnetic field. If successful, it could change the way military and commercial planes and drones navigate and open up a new market after decades of the idea working only in theory.
Such efforts have previously foundered in part because it is especially hard to separate the magnetic resonance created by the Earth from that of the plane itself – something refined, complex algorithms can potentially help solve, McAlpin said. That has helped reduce the computing power required too: McAlpin said the algorithms can now be tested on standard laptops on board flights. “We believe that we could have something in the next 12 to 18 months that could be used pretty widely,” Sovada said.