An efficient recognition method for turbulence intensity via random matrix theory

Haiyang Yu; Xu Zhou; Chunyi Chen; Xiaojuan Hu

doi:10.1117/12.2668081

20 April 2023 An efficient recognition method for turbulence intensity via random matrix theory

Haiyang Yu, Xu Zhou, Chunyi Chen, Xiaojuan Hu

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126021Y (2023) https://doi.org/10.1117/12.2668081
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

In this paper, a novel recognition method based on random matrix is proposed for different turbulence intensity. To reflect the degree of atmospheric turbulence, the continuous product form of phase screens is taken into consideration. After calculated the statistical distribution using random matrix theory, the fitting effect of statistical distribution determines the differences of turbulence. Also, based on the data-driven idea, the eigenvalue and singular values of phase screens are described as a whole. According to the adaptability of large dimensional random matrices, the Ring Law and M-P Law breaks through the assumptive restriction of infinite sample, thus building a significant model for potential changes of weak turbulence. The simulation experiments validate that the big data technology is effective attempt for atmospheric turbulence recognition.

Citation Download Citation

Haiyang Yu, Xu Zhou, Chunyi Chen, and Xiaojuan Hu "An efficient recognition method for turbulence intensity via random matrix theory", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126021Y (20 April 2023); https://doi.org/10.1117/12.2668081

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