Delay-Augmented Spectrometry for Target Classification Using a Frequency-Comb LiDAR

Yu Han; David Salido-Monzú; Andreas Wieser

doi:10.1364/cleo_si.2022.sf2f.5

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JOURNAL ARTICLE

Delay-Augmented Spectrometry for Target Classification Using a Frequency-Comb LiDAR

Yu Han David Salido-Monzú Andreas Wieser

Year: 2022 Journal: Conference on Lasers and Electro-Optics Vol: 27 Pages: SF2F.5-SF2F.5

DOI: 10.1364/cleo_si.2022.sf2f.5

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Abstract

We demonstrate LiDAR-based remote spectrometry of natural targets augmented with delay spectra using an ultra-broadband frequency comb. Material-dependent spectrally-resolved delays with an equivalent sensitivity better than 100 µ m complement reflectance signatures for enhanced target classification.

Keywords:

Lidar Broadband Remote sensing Sensitivity (control systems) Mass spectrometry Reflectivity Ranging Materials science Computer science Environmental science Optics Physics Geology Electronic engineering Telecommunications Engineering

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Delay-Augmented Spectrometry for Target Classification Using a Frequency-Comb LiDAR

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