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We report our recent studies on the use of Neural Networks to process the measured Brillouin gain spectrum (BGS) from Brillouin Optical Time Domain Analyzer (BOTDA) and extract temperature information along fiber under test (FUT). Artificial Neural Network (ANN) is trained with ideal Lorentizian BGS before it is used for temperature extraction. Its performance is evaluated by comparison to conventional...
A novel setup for coherent-detection-assisted Brillouin optical time domain analysis (BOTDA) is proposed and demonstrated. Performance enhancement is enabled by a power-controllable local oscillator (LO) generated using single-side-band (SSB) modulation. Through employing a commercial coherent receiver and polarization diversity scheme, the Brillouin gain traces carried on a stable intermediate frequency...
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