Acquiring reflective polarization from arbitrary multi-layer surface based on Monte Carlo simulation

A novel Monte Carlo model is proposed to acquire the reflective polarization information from a rough surface with arbitrary layers and profiles. Based on the micro-facets theory, the local normal vectors can be randomly sampled from the normal vector distribution of each layer. The incident light that propagates inside of the multi-layer media will be traced until being collected after leaving the surface or be ignored due to lacking enough energy. The simulated results (by our proposed theoretical model) agree well with the reported measured data and the analytical models from SCATMECH, which demonstrates the correctness and effectiveness of our model. Based on our model, the effects of the surface layer number, the surface geometry, the incident wavelength and polarization states of incidence on the reflective polarization from multi-layer surfaces have been analyzed in detail, which can be a guide in tasks such as target detection and so on.