weighted singular value decomposition
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2021 ◽  
Vol 11 (4) ◽  
pp. 1928
Author(s):  
Khurram Naeem ◽  
Bok Hyeon Kim ◽  
Dong-Jin Yoon ◽  
Il-Bum Kwon

We propose a weighted singular value decomposition (WSVD) to reduce the random noise in the Rayleigh backscattering signal of the phase-sensitive optical time domain reflectometry (Φ-OTDR) to enhance the detection performance of the distributed vibration sensing. A 2D image is formed by assembling the raw Rayleigh backscattering traces into a matrix form, and slowly varying fluctuation and random noise can be removed using the WSVD. Consequently, the location information and the frequency of vibration induced by the external vibration event can be extracted. A vibration event with 9 m spatial resolution is detected along a 2.4 km single mode fiber. The signal-to-noise ratio (SNR) of location information for the 102 Hz physical vibration and the 525 Hz acoustic vibration was found to be 10.7 and 12.2 dB, respectively. The SNR of the vibration events demonstrate an increase of 6–7 dB compared to the conventional method, showing the excellent denoising capability of this new approach.


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