Mie-Scattering-Based Simulation of Underwater Multispectral LiDAR Propagation and Optimal Wavelength Selection

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Authors: Zhichao Chen, Zhaoyan Liu, Shi Qiu, Hailong Zhang, Yuwei Chen, Weiyuan Yao, Tong Zhang, Yu Zhang, Hongjia Cheng, Feihong Wang, Zhan Shu
Cited by: 1
References: 35

Abstract

Multispectral LiDAR can simultaneously obtain distance and spectral information and shows great potential for underwater detection. However, absorption and scattering caused by suspended particles in water lead to energy attenuation and multiple scattering, which affect echo intensity and ranging accuracy, while the propagation characteristics under multi-wavelength conditions remain insufficiently studied. In this study, a simplified underwater propagation simulation model for multispectral LiDAR is established based on the equivalent spherical-particle assumption, combining Mie scattering theory with a semi-analytical Monte Carlo method. The effects of particle size on echo intensity and ranging error are analyzed under fixed concentration conditions. Based on this model, a detection-threshold-constrained optimal wavelength selection criterion is formulated. Multi-distance analysis (3, 5, 8, and 15 m) confirms that the preferred wavelength is primarily governed by particle size and remains stable across depths. The results show that the optimal detection wavelength shifts with particle size, being about 560 nm for fine particles and gradually moving toward the 400–480 nm blue–green band for larger particles. Experimental validation shows that the simulation-based ranging correction reduces RMSE by 9.4–25.9% (average 18.1%) and MAE by 11.8–29.7% (average 22.0%) across five experimental distances. The results provide a preliminary reference for wavelength selection in multispectral LiDAR systems under simplified conditions.

Fields of Study & Subjects

Remote Sensing and LiDAR Applications Advanced Optical Sensing Technologies Oil Spill Detection and Mitigation

Publication details

Journal / source
Photonics
Publisher
MDPI AG
Volume
13
Issue
5
Pages
423–423
Publication date
24 April 2026
Language
EN