Low SNR multimirror Fabry–Perot pressure sensor optic spectrum signal analysis and demodulation via SVM-KNN regressors

Author:

Yang Yiguang1,Geng Dahe,Chen Hao,Li Xujin1,Zhang Weihong1,Yuan YiboORCID,Meng Xiangqian,Wenhong Li

Affiliation:

1. Laoshan Laboratory

Abstract

We demonstrate an ensemble learning based method to solve the problem of low SNR Fabry–Perot sensor spectrum signal demodulation. Taking the eight-layer approximate coefficients of a multilevel discrete wavelet transform as input features, an ensemble model that combines multiple SVM and KNN learners is trained. Bootstrap and booting techniques are introduced for better modeling performance and stability. It is shown that the performance of the proposed ensemble model based on SVM-KNN regressors is excellent; an accuracy of 0.46%F.S. relative mean error is achieved. This method could provide insight into the construction of a large scale fiber based Fabry–Perot sensor network.

Funder

Key Laboratory of Ocean Observation Technology

National Natural Science Foundation of China

Publisher

Optica Publishing Group

Subject

Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering

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