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Light Shaken, Stirred to Help Autonomous Vehicles Better Scan for Nearby Fast-Moving Objects

By Purdue University News

July 23, 2020

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Researchers at Purdue University and the Swiss Federal Institute of Technology in Lausanne have developed a technique for realizing higher-resolution detection of nearby fast-moving objects in frequency modulated continuous wave (FMCW) LiDAR, a critical advance for autonomous vehicles.

The method employs acoustic waves to enable faster tuning of FMCW LiDAR's components.

The researchers integrated aluminum-nitride microelectromechanical systems (MEMS) transducers to modulate a microcomb—a laser beam split into a comb of multiple wavelengths—at high frequencies, using an optical isolator.

A phased MEMS transducer array stirs light at gigahertz frequencies by projecting a corkscrew-like stress wave into a silicon chip.

The researchers suggested the technology could stimulate microcomb applications in power-critical systems in space, datacenters, and portable atomic clocks, or in extreme environments like those with cryogenic temperatures.

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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA


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