Open AccessComparison and application of wavelet transform and Kalman filtering for denoising in δ^13CO_2 measurement by tunable diode laser absorption spectroscopy at 2008 µm
Author(s) -
Muye Niu,
Pin Han,
Lian-ke Song,
Hao Dian-zhong,
Jinghu Zhang,
Lili Ma
Publication year - 2017
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.25.00a896
Subject(s) - noise reduction , optics , noise (video) , tunable diode laser absorption spectroscopy , materials science , kalman filter , signal (programming language) , absorption (acoustics) , filter (signal processing) , wavelet transform , wavelet , laser , spectroscopy , computer science , physics , acoustics , tunable laser , artificial intelligence , computer vision , quantum mechanics , image (mathematics) , programming language
We propose to use the wavelet transform and Kalman filter methods for processing noise in δ 13 CO 2 measurement using laser absorption spectroscopy at 2.008 µm and they have been shown to be useful tool for reducing the intrinsic noise of the optical system. Through the performance comparison and analysis of these two denoising techniques for the intrinsic noise reduction of optical system, it can be found that the Kalman filter is a more suitable approach for the extraction of gas isotope measurement signal from a contaminated signal.