Autonomous vehicles that rely on light-based image sensors often struggle to see through blinding conditions, such as fog. But MIT researchers have now developed a system that could help steer driverless cars when traditional methods fail, MIT News reports.
The new system uses sub-terahertz wavelengths, which are between microwave and infrared radiation on the electromagnetic spectrum. They can be detected through fog and dust clouds with ease, whereas the infrared-based LiDAR imaging systems used in autonomous vehicles struggle.
But implementing sub-terahertz sensors into driverless cars is challenging. Sensitive, accurate object-recognition requires a strong output signal. Traditional systems are large and expensive. Smaller ones exist, but they produce weak signals.
In a paper published online on Feb. 8 by the IEEE Journal of Solid-State Circuits, the researchers describe a chip (pictured above) that’s orders of magnitude more sensitive, meaning it can better capture and interpret sub-terahertz wavelengths.
“A big motivation for this work is having better ‘electric eyes’ for autonomous vehicles and drones,” says co-author Ruonan Han, an associate professor of electrical engineering and computer science, and director of the Terahertz Integrated Electronics Group in the MIT Microsystems Technology Laboratories (MTL).