Multi-spectral underwater lidar evaluation based on semi-analytical Monte Carlo methods

Underwater multi-spectral lidar based on supercontinuum laser sources, leveraging multi-spectral illumination for enhanced seawater optical profiling and target detection, remains underexplored despite these sources' transformative potential in marine sensing. In this research, we present a semi-analytical Monte Carlo simulation (MC) framework based on bio-optical models to investigate its performance in complex aquatic environments. The simulator reconstructs seawater inherent optical properties (IOPs) via configurable parameters to analyze spectral signal characteristics. Numerical experiments evaluating 400-800 nm bands in different ecosystems provide the following results. (1) The sensitivity of laser wavelength to phytoplankton exhibits pronounced variations. A strong positive correlation is observed between the lidar attenuation coefficient (<i>k</i>_{<i>l</i><i>i</i><i>d</i><i>a</i><i>r</i>}) and the chlorophyll concentration (Chl), with R values reaching 0.9934 at 400 nm and 0.9783 at 600 nm. In particular, this correlation declines sharply to -0.01 at 800 nm, indicating a wavelength-dependent decoupling of optical attenuation from phytoplankton biomass in near-infrared regimes. (2) The use of a supercontinuum laser for underwater target detection can effectively distinguish the spectral characteristics of the target object and realize the identification of the target species during lidar detection. This work establishes a computational foundation for next-generation marine multi-spectral lidar development, providing critical insights into subsurface radiation physics while demonstrating supercontinuum lidar's dual capability in simultaneous water column characterization and benthic target identification.