Light-based image sensors in autonomous vehicles frequently struggle to see through blinding conditions such as fog. However, researchers have developed a sub-terahertz-radiation receiving system that could aid in the navigation of driverless cars if traditional methods fail.
Sub-terahertz wavelengths on the electromagnetic spectrum between microwave and infrared radiation can easily penetrate fog and dust clouds, whereas infrared-based LiDAR imaging systems used in autonomous vehicles struggle. A sub-terahertz imaging system detects objects by sending an initial signal through a transmitter. A receiver then measures the absorption and reflection of the rebounding sub-terahertz wavelengths. It sends a signal to a processor, which recreates the object’s image.
However, incorporating sub-terahertz sensors into driverless cars is difficult. A substantial output baseband signal from the receiver to the processor enables sensitive, accurate object recognition. Traditional systems, comprised of discrete components that generate such signals, are extensive and costly. On-chip sensor arrays are smaller, but they produce weak signals.
The researchers created a two-dimensional, sub-terahertz receiving array on a more sensitive chip, which means it can capture and interpret sub-terahertz wavelengths even in high signal noise. The researchers reduced the size of the heterodyne detectors (a scheme of independent signal-mixing pixels) so that many of them could fit on a single chip.