• Title/Summary/Keyword: Scatting Noise

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Analysis Study of Mobile LiDAR Performance Degradation in Rainfall Based on Real-World Point Cloud Data (강우 시 모바일 LiDAR 성능저하에 대한 실측 점군데이터 기반 해석 연구)

  • Youngmin Kim;Bumjin Park
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.5
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    • pp.186-198
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    • 2024
  • LiDAR is a key sensor used in autonomous vehicles, and its range of applications is expanding because it can generate 3D information and is relatively robust to various environmental factors. However, it is known that LiDAR performance is degraded to some extent due to signal attenuation and scattering by raindrops during rain, and thus the need for analysis of factors affecting rainfall in road environment detection and utilization using LiDAR has been confirmed. In this study, we analyze how signal attenuation and scattering, known as factors degrading LiDAR performance during rain, cause performance degradation based on real data. We acquire data using facilities that utilize high-luminosity retroreflective sheeting in indoor chamber where quantity of rainfall can be controlled, and quantitatively confirm the degradation of LiDAR performance during rain by interpreting it from the perspective of signal attenuation and scattering. According to the point cloud distribution and performance analysis results, LiDAR performance deteriorates due to signal attenuation and scattering caused by rain. Specifically, the quantitative performance analysis shows that LiDAR experiences a decrease in intensity primarily due to signal attenuation from rain, as well as a reduction in NPC and intensity due to signal scattering effects, along with an increase in measurement distance error.