Frequency-modulated continuous-wave LiDAR compressive depth-mapping

Daniel J. Lum*, Samuel H. Knarr, John C. Howell

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Scopus citations


We present an inexpensive architecture for converting a frequency-modulated continuous-wave LiDAR system into a compressive-sensing based depth-mapping camera. Instead of raster scanning to obtain depth-maps, compressive sensing is used to significantly reduce the number of measurements. Ideally, our approach requires two di erence detectors. Due to the large flux entering the detectors, the signal amplification from heterodyne detection, and the e ects of background subtraction from compressive sensing, the system can obtain higher signal-to-noise ratios over detector-array based schemes while scanning a scene faster than is possible through raster-scanning. Moreover, by e ciently storing only 2m data points from m < n measurements of an n pixel scene, we can easily extract depths by solving only two linear equations with e cient convex-optimization methods.

Original languageAmerican English
Pages (from-to)15420-15435
Number of pages16
JournalOptics Express
Issue number12
StatePublished - 11 Jun 2018

Bibliographical note

Publisher Copyright:
© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement


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