Empirical Comparison of Full-Waveform Lidar Algorithms

TLDR

As third‑party lidar software manufacturers increasingly support full‑waveform data, users face the question of which algorithms to implement, considering output quality, processing speed, application suitability, robustness to parameter choices, and user experience. The paper aims to provide an empirical method for comparing range extraction and discrimination performance of lidar waveform algorithms in a practical, operational setting using a ranging‑lab with adjustable targets and precise separations. The method employs a ranging‑lab with multiple adjustable screen targets at precisely measured separations to empirically assess range extraction and discrimination performance of different lidar waveform algorithms. The study compared three algorithms from the literature, revealing distinct performance differences and demonstrating that no single algorithm or parameter set is universally optimal, with choices being highly application‑dependent.

Abstract

As third-party lidar software manufacturers are increasingly adding support for full-waveform data, a common question is which algorithm(s) to implement. To this end, a new approach is needed to compare and contrast various lidar waveform processing strategies from a practical, operational perspective. Quality and type of information output, processing speed, suitability for particular applications, robustness against poor parameter selection, and more subjective measures related to user experience are of interest. This paper describes a new empirical method of comparing range extraction and discrimination performance of different algorithms, based on a ranging-lab setup with multiple, adjustable screen targets, with precisely-measured separations. We present the results of comparing three different algorithms described in the scientific literature. The results show distinct differences and also indicate that there is no “one-size-fits-all” approach: the choice of a specific algorithm and adjustable parameter settings are highly application-dependent.