Giving keener “electric eyesight” to autonomous vehicles

On-chip system that detects signals at sub-terahertz wavelengths could help steer driverless cars through fog and dust.

Autonomous vehicles relying on light-based image sensors often struggle to see through blinding conditions, such as fog. But MIT researchers have developed a sub-terahertz-radiation receiving system that could help steer driverless cars when traditional methods fail.

Sub-terahertz wavelengths, which are between microwave and infrared radiation on the electromagnetic spectrum, can be detected through fog and dust clouds with ease, whereas the infrared-based LiDAR imaging systems used in autonomous vehicles struggle. To detect objects, a sub-terahertz imaging system sends an initial signal through a transmitter; a receiver then measures the absorption and reflection of the rebounding sub-terahertz wavelengths. That sends a signal to a processor that recreates an image of the object.

But implementing sub-terahertz sensors into driverless cars is challenging. Sensitive, accurate object-recognition requires a strong output baseband signal from receiver to processor. Traditional systems, made of discrete components that produce such signals, are large and expensive. Smaller, on-chip sensor arrays 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 two-dimensional, sub-terahertz receiving array on a chip that’s orders of magnitude more sensitive, meaning it can better capture and interpret sub-terahertz wavelengths in the presence of a lot of signal noise

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Veröffentlichung:
19. Februar 2019