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March 14, 2026PhotoniX3 citationsOpen Access

Lidar bathymetry over 140 m with polarization noise suppression

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QGQiuling GuHZHongkai ZhaoYCYatong Chen

Key Points

  • The study aims to improve the accuracy of lidar bathymetry for depths over 140 m.
  • Utilized a lidar emulator to optimize system parameters.
  • Employed a 486 nm laser for enhanced bottom signal detection.
  • Implemented polarization detection to suppress background noise.
  • Achieved the deepest detectable depth over 140 m in lidar bathymetry.
  • Demonstrated a 1.6 times SNR enhancement of cross-polarized signals at depths over 100 m.
  • Suppressed 68.7% of background noise using the cross-polarized channel.

Abstract

Abstract Lidar provides unique capabilities for integrated land-sea surveying, delivering highly efficient and accurate bathymetric and topographic measurements. However, depth challenges remain for existing lidar systems due to the weak signal of water bottom and interference from background noise. Here, we demonstrate, to the best of our knowledge, the deepest detectable depth over 140 m ever reported through lidar bathymetry in the South China Sea. Through a comprehensive lidar emulator, key system parameters were optimized to enhance the bottom signal with a 486 nm laser. Additionally, the emulator formulated the polarization detection to suppress the background noise including dark counts and water column backscatter, owing to their polarized differences from bottom signals. Experimental results demonstrated that the SNR enhancement of cross-polarized signals is 1.6 times that of the total signals at depths exceeding 100 m. Meanwhile, 68.7% of the background noise was suppressed by utilization of the cross-polarized channel. The lidar bathymetric data after multiple scattering corrections showed good agreement with shipborne Acoustic Doppler Current Profiler measurements, with a root mean square relative deviation (RMSRD) of 5.23%. The research offers implications for filling knowledge gaps across continental shelves and delivers new insights for improving seafloor monitoring and benthic mapping.

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Cite This Study

Gu et al. (2026) studied this question.

synapsesocial.com/papers/69b4ba0818185d8a398027achttps://doi.org/10.1186/s43074-026-00231-9
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