Coherent fading suppression of distributed acoustic sensing based on time–frequency domain linkage algorithm

Abstract Due to the inherent characteristic of coherent fading phenomenon, the performance of distributed acoustic sensing system will be severely degraded, producing anomalous information and positioning errors. In order to suppress the influence of this phenomenon, the data array of demodulated results is obtained after processing the collected distributed Rayleigh scattering signals along the sensing fiber, which can be utilized to construct a two-dimension (2D) image with the time–distance domain information. Thus, this allows us to remove the abnormal information that are introduced by fading noise. Based on this principle, a morphology compositional analysis (MCA) scheme, an effective time–frequency domain linkage algorithm, is applied to the constructed 2D images to enhance the sensing accuracy. Compared with traditional methods including the 2D mean value filter (MVF) and 2D wavelet transform (WT), the proposed method makes full use of the independence of image source property and abnormity feature so that the abnormal information caused by the coherent fading can be eliminated without deteriorating the source information along the sensing fiber. Experimental results show that the anomaly rate of the time–distance domain information along the sensing fiber for the proposed method, the MVF method and the WT method can be reduced by 92.43%, 65.05% and 70.18% respectively. In addition, the isolation degree of the MCA, MVF and WT methods are 41, 16.02 and 23.35 times higher than that treated by traditional method, respectively. Also, the stability of the time-domain vibration can be improved and the spatial resolution would not be influenced by the proposed method compared with the traditional method. This scheme will promote the development of distributed acoustic sensor system with high-accuracy and high-quality without any hardware modification.