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Quantifying the accuracy of FRI-based LIDAR waveform analysis

Third generation full-waveform (FW) LIDAR systems collect time-resolved 1D signals generated by laser pulses reflecting off of intercepted objects. From these signals, scene depth profiles along each pulse path can be readily constructed. Using the conventional sampling process, however, massive amounts of data are typically required in order to achieve acceptable depth and spatial resolutions, and this data must be stored, transmitted, and processed. We have previously shown that such signals can be sampled at sub-Nyquist rates by using a finite rate of innovations (FRI) model. That work, however, used LIDAR data for which ground-truth distances were not available and it was therefore not possible to fully evaluate the range precision of an FRI-based representation. Here, we apply the proposed methodology to carefully ground-truthed laboratory data in order to better characterize its capabilities and limitations.