Signal-to-noise ratio improvement of Brillouin optical time domain analysis system based on empirical mode decomposition and finite impulse response

Abstract

We propose a denoising algorithm based on empirical mode decomposition (EMD) and finite impulse response (FIR) to improve the signal-to-noise ratio (SNR) of Brillouin optical time domain analysis. Denoising results indicate EMD-FIR can effectively reduce noise, and the maximum SNR improvement is 11.69 dB, which is 4.98 dB and 4.26 dB larger than the maximum SNR improvement of wavelet and Butterworth. The temperature uncertainty along the heated section is reduced to 0.62°C by EMD-FIR. The improvement of SNR opens opportunities to apply high measurement accuracy to Brillouin optical time domain analysis and other distributed sensing fields.