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The Wavelet Filtration Denoising in the Raman Distributed Temperature Sensing
Up to now a Distributed optical fiber Temperature Sensor (DTS) based on the
Raman scattering exhibits a relatively low characteristic causes sharp
temperature changes to be improved. Modeling metrological characteristics has
a long history but essential progress did not achieved. This paper presents
a novel technique of the extremal filtration developed to improve the DTS
temperature and partially spatial resolution. The algorithm is based on
wavelet transformation of backscattered anti-Stokes and Stokes signals and
deconvolution on high-frequency components with total regularization of
variations. Experimental results correctly agree with real modeling values
with denoising ones. The advantage is the ability to reconstruct temperature
with 0.01 degree accuracy at fixed spatial resolution. We present a lot of
simulations and figures demonstrated the efficacy of the proposed technique.