Analysis of combined moving-average moving-differential algorithms to enhance SNR in distributed optical fiber acoustic sensors

• Utilizes moving-average moving-differential (MA-MD) algorithm to overcome the low SNR challenge in distributed optical fiber acoustic sensing (DAS). • Investigate the best window and interval size for the combined algorithm for direct and coherent detection DAS systems, with various pulse widths • The algorithm is applied on the data from the disturbance with mixed frequency acoustic signal. • The MA-MD algorithm holds the potential to improve the SNR in both direct detection and coherent DAS systems. Moving-average and moving-differential (MA-MD) techniques are widely used to process signals from distributed optical fiber acoustic sensors (DAS). However, the optimal combination of window and interval sizes to achieve the best signal-to-noise ratio (SNR), especially for signals with mixed frequency components, has yet to be studied. The study investigates the ideal combination of window and interval sizes to enhance SNR in direct and coherent detection-based DAS systems. The optimisation is further extended to multiple pulse widths. The results show that the coherent detection DAS achieves a higher optimal SNR than the direct detection DAS and system with shorter pulse width achieved higher optimal SNR. When optimised, the MA-MD enhanced the SNR by up to 1.68 dB compared to the conventional and normalised differential methods. To the best of our knowledge, this is the first study that demonstrate the applicability of the MA-MD algorithm in real-world DAS applications with mixed-frequency acoustic signals and provide valuable insights to improve DAS performance.