Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition

A signal-extraction algorithm for photon-counting LiDAR is proposed to accurately measure mountainous terrain elevation during daylight. The algorithm exponentially scales distances among photons, employs the shortest path length between photons, and applies a maximum between-class variance method to extract the signals from dense connected point clouds. Simulated and advanced topographic altimeter system (ATLAS) data tests show the algorithm's accuracy surpassing 0.9 in high-relief areas during the day. This method utilizes global and local data consistencies to mitigate terrain fluctuations effects and accurately extract mountainous signals improving signal photon extractions in steep topography under varying background photon-counting rates.

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Publication Details

Journal
Optics Express
Published
2024-12-04
DOI
https://doi.org/10.1364/oe.540437
Citations
2
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
1.01

Funders

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article

Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition

Ren Liu, Ruikai Xue, Rujia Ma, Wei Kong et al.
2 citations
Optics Express
Advanced Optical Sensing Technologies
1.01
article

Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition

Ren Liu, Ruikai Xue, Rujia Ma, Wei Kong, Genghua Huang
article en
2 citations

Abstract

A signal-extraction algorithm for photon-counting LiDAR is proposed to accurately measure mountainous terrain elevation during daylight. The algorithm exponentially scales distances among photons, employs the shortest path length between photons, and applies a maximum between-class variance method to extract the signals from dense connected point clouds. Simulated and advanced topographic altimeter system (ATLAS) data tests show the algorithm's accuracy surpassing 0.9 in high-relief areas during the day. This method utilizes global and local data consistencies to mitigate terrain fluctuations effects and accurately extract mountainous signals improving signal photon extractions in steep topography under varying background photon-counting rates.

Optics ExpressVol. 32(26)
Yunnan Normal University (CN), Hefei University (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 18%
Advanced Optical Sensing Technologies
1.01
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Terrain signal photon-extraction algorithm for photon-counting LiDAR based on an adjustable length definition — Ren Liu, Ruikai Xue, et al. · Optics Express (2024) | TGRS Research Map | TGRS