Monte Carlo simulation of polarization of light back-scattered from randomly rough surfaces

• Autorzy: Jiang Yuxiang , Li Zhenhua

Identyfikatory

DOI

10.37190/oa230105

• Języki publikacji: EN

Abstrakty

EN

Laser detection devices obtain target information from back-scattered light, such as lidar. The recognition rate can be improved by analyzing intensity and polarization of echo signal. In this paper, Monte Carlo method is used to generate a large number of randomly rough surfaces to simulate targets. Every rough surface is discretized into a large number of micro-surface elements. Stokes parameters of back-scattered light are calculated by numerical integration. Incident light is p-, s-, 45° linearly polarized light and right-hand circularly polarized light, respectively. Numerical results show that when s- and p-linearly polarized light incident on a metal rough surface, back-scattered light appears circularly polarized component. Metal rough surface resembles a wave plate with phase difference, with the fast axis parallel or perpendicular to the 45° direction. When linearly polarized light is incident on dielectric rough surface, back-scattered light has no circularly polarized component. Experimental data are consistent with the numerical results. The above research provides a new basis for laser detection device to identify metal targets from the environmental background.

Słowa kluczowe

EN

backscattering; randomly rough surface; Stokes parameters; Monte Carlo method; polarized light

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2023
• Tom: Vol. 53, nr 1
• Strony: 65--85
• Opis fizyczny: Bibliogr. 39 poz., rys.

Twórcy

autor

Jiang Yuxiang

• College of Science, Nanjing University of Science and Technology, Nanjing 210094, China
• Engineering Training Centre, Nanjing University of Science and Technology, Nanjing 210094, China

autor

Li Zhenhua

• College of Science, Nanjing University of Science and Technology, Nanjing 210094, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).