University of Oulu

Turov, A. T., Konstantinov, Y. A., Barkov, F. L., Korobko, D. A., Zolotovskii, I. O., Lopez-Mercado, C. A., & Fotiadi, A. A. (2023). Enhancing the Distributed Acoustic Sensors’ (DAS) Performance by the Simple Noise Reduction Algorithms Sequential Application. Algorithms, 16(5), 217.

Enhancing the distributed acoustic sensors’ (DAS) performance by the simple noise reduction algorithms sequential application

Saved in:
Author: Turov, Artem T.1,2; Konstantinov, Yuri A.1; Barkov, Fedor L.1;
Organizations: 1Perm Federal Research Center of the Ural Branch of the Russian Academy of Sciences (PFRC UB RAS), 13a Lenin Street, 614000 Perm, Russia
2General Physics Department, Applied Mathematics and Mechanics Faculty, Perm National Research Polytechnic University, Prospekt Komsomolsky 29, 614990 Perm, Russia
3S.P. Kapitsa Research Institute of Technology, Ulyanovsk State University, 42 Leo Tolstoy Street, 432970 Ulyanovsk, Russia
4Scientific Research and Advanced Studies Center of Ensenada (CICESE), Ensenada 22860, BC, Mexico
5Electromagnetism and Telecommunication Department, University of Mons, B-7000 Mons, Belgium
6Optoelectronics and Measurement Techniques Unit, University of Oulu, 90570 Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 3.5 MB)
Persistent link:
Language: English
Published: Multidisciplinary Digital Publishing Institute, 2023
Publish Date: 2023-09-19


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.

see all

Series: Algorithms
ISSN: 1999-4893
ISSN-E: 1999-4893
ISSN-L: 1999-4893
Volume: 16
Issue: 5
Article number: 217
DOI: 10.3390/a16050217
Type of Publication: A1 Journal article – refereed
Field of Science: 114 Physical sciences
Funding: A.A.F. is supported by the European Union’s Horizon 2020 research and innovation program (Individual Fellowship, H2020-MSCA-IF-2020, #101028712).
EU Grant Number: (101028712) HiFi Brilliancy - HIgh-speed FIbre-based BRILLouIn ANalyzer for endosCopY
Copyright information: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (