4.5 Article

Scattering direction sampling methods for polarized Monte Carlo simulation of oceanic lidar

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APPLIED OPTICS
卷 62, 期 23, 页码 6253-6263

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Optica Publishing Group
DOI: 10.1364/AO.494894

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Monte Carlo techniques are widely used in polarized light simulation. There are two main types of sampling strategies for scattering direction based on different preconditions: scalar sampling method and polarized sampling approaches. Efficient scattering sampling method is essential for the coupling simulation of the atmosphere and ocean in oceanic lidar polarized simulation.
Monte Carlo techniques have been widely applied in polarized light simulation. Based on different preconditions, there are two main types of sampling strategies for scattering direction: one is the scalar sampling method; the others are polarized sampling approaches, including the one-and two-point rejection methods. The polarized simulation of oceanic lidar involves a variety of mediums, and an efficient scattering sampling method is the basis for the coupling simulation of the atmosphere and ocean. To determine the optimal scattering sampling method for oceanic lidar simulation, we developed a polarized Monte Carlo model and simulated Mie scattering, Rayleigh scattering, and Petzold average-particle scattering experiments. This simulation model has been validated by comparison with Ramella-Roman's program [Opt. Express 13, 4420 (2005)], with differences in reflectance and transmittance Stokes less than 1% in Mie scattering. The simulation results show these scattering sampling meth-ods differ in runtime, scattering angle distributions, and reflectance and transmittance Stokes. Considering the current simulation accuracy of oceanic lidar, the differences in reflectance and transmittance Stokes are acceptable; thus, the runtime becomes the main evaluation factor. The one-point rejection method and scalar sampling method are preferable for the oceanic lidar polarized simulation. Under complex atmosphere-ocean coupling systems, scalar sampling methods may be a better choice since the calculation process of the sampling is independent of the incident Stokes vector. & COPY; 2023 Optica Publishing Group

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