Noise Reduction Based on Adaptive Prediction Fitting Algorithm for a Heterodyne Φ-OTDR System

Aiming to reduce the noise better in distributed optical fiber vibration sensing system, an adaptive predictive filtering algorithm is proposed to improve the overall signal-to-noise ratio (SNR) of vibration detection. A phase-sensitive optical time domain reflectometric ( $\Phi $ -OTDR) system based on heterodyne detection with dual AOMs is designed to reduce the requirement of DAQ high sampling rate, and an adaptive prediction noise reduction method based on normalized least mean square (NLMS) is adopted to reduce the non-stationary noise. Experimental results show that the SNR is increased from 8.14dB to 22.31dB. Compared with moving difference average method, wavelet denoising method and Prewitt edge detection method, the SNR of the adaptive prediction noise reduction algorithm is the highest, which would have potential application in disturbance detection under a strong noise environment.