Research on singular value decomposition denoising algorithm on polarization mode dispersion measurement

Yalei Chu; Yangan Zhang; Xueguang Yuan; Xiaomin Ren

doi:10.1117/12.2506292

15 November 2018 Research on singular value decomposition denoising algorithm on polarization mode dispersion measurement

Yalei Chu, Yangan Zhang, Xueguang Yuan, Xiaomin Ren

Author Affiliations +

Proceedings Volume 10964, Tenth International Conference on Information Optics and Photonics; 109645A (2018) https://doi.org/10.1117/12.2506292
Event: Tenth International Conference on Information Optics and Photonics (CIOP 2018), 2018, Beijing, China

Abstract

In order to eliminate the noise in the polarization mode dispersion(PMD)measurement system by the fixed analyzer method and improve the measurement accuracy, this paper applies singualr value decomposition(SVD) denoising algorithm to polarization mode dispersion measurement scheme. First, construct Hankel matrix in term of a discrete signal sequence, and it was decomposed into a number of matrixes by singular value. Second, divide singular values into two groups: valid group and noise group and fit the valid signal characteristic curve and the noise characteristic curve. Then, calculate the fitting error, and define the minimal order of fitting error as valid order. Finally, reconstruct the signal. The experiments compare results based on the SVD filtering method, Butterworth filtering method and commercial instruments. The results show that this method is suitable in different types and lengths of fiber. The measurement accuracy was improved obviously.

Citation Download Citation

Yalei Chu, Yangan Zhang, Xueguang Yuan, and Xiaomin Ren "Research on singular value decomposition denoising algorithm on polarization mode dispersion measurement", Proc. SPIE 10964, Tenth International Conference on Information Optics and Photonics, 109645A (15 November 2018); https://doi.org/10.1117/12.2506292

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