This work presents a detailed review of the development of distributed acoustic sensors (DAS) and their newest scientific applications. It covers most areas of human activities, such as the engineering, material, and humanitarian sciences, geophysics, culture, biology, and applied mechanics. It also provides the theoretical basis for most well-known DAS techniques and unveils the features that characterize each particular group of applications. After providing a summary of research achievements, the paper develops an initial perspective of the future work and determines the most promising DAS technologies that should be improved.

Moving differential and dynamic window moving averaging are simple and well-known signal processing algorithms. However, the most common methods of obtaining sufficient signal-to-noise ratios in distributed acoustic sensing use expensive and precise equipment such as laser sources, photoreceivers, etc., and neural network postprocessing, which results in an unacceptable price of an acoustic monitoring system for potential customers. This paper presents the distributed fiber-optic acoustic sensors data processing and noise suppression techniques applied both to raw data (spatial and temporal amplitude distributions) and to spectra obtained after the Fourier transform. The performance of algorithms’ individual parts in processing distributed acoustic sensor’s data obtained in laboratory conditions for an optical fiber subjected to various dynamic impact events is studied. A comparative analysis of these parts’ efficiency was carried out, and for each type of impact event, the most beneficial combinations were identified. The feasibility of existing noise reduction techniques performance improvement is proposed and tested. Presented algorithms are undemanding for computation resources and provide the signal-to-noise ratio enhancement of up to 13.1 dB. Thus, they can be useful in areas requiring the distributed acoustic monitoring systems’ cost reduction as maintaining acceptable performance while allowing the use of cheaper hardware.

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Modal birefringence (the difference between the effective refractive indices of orthogonal polarisation modes) is one of the key parameters of anisotropic single-mode fibres, characterising their ability to preserve a linearly polarised state of input light. This parameter is commonly measured using short pieces of fibre, but such procedures are destructive and allow the birefringence to be determined only at the ends of long fibres. In this study, polarised light Brillouin reflectometry is used to assess birefringence uniformity throughout the length of an anisotropic fibre.

A new method of Brillouin spectra post-processing, which could be applied in modern distributed optical sensors: Brillouin optical time domain analyzers/reflectometers (BOTDA/BOTDR), has been demonstrated. It operates by means of the correlation analysis performed with special technique («backward-correlation»). It does not need any additional data for time or space averaging and operates with the single spectrum only. We have simulated the method accuracy dependence on signal-to-noise ratio (SNR) and other parameters. It is shown that the new method produces better results at low SNRs than conventional technique, based on finding of Brillouin spectrum maximum, do. These results are in a good agreement with the experiment. Finally, we have estimated the performance of the new method for its application in polarization-BOTDA set-up for a polarization maintaining (PM) fiber modal birefringence distributed study.