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.
Bibliographical noteFunding Information:
Air-Force O ce of Scientific Research (AFOSR) (FA9550-16-1-0359).
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