Reference matrix self-correction for perturbation compensation in MFDD-DAS

Multi-Frequency Database Demodulation (MFDD) combined with chirped-pulse (CP) phase-sensitive OTDR (φ-OTDR) has been recently presented as a method for distributed acoustic sensing (DAS) systems that can reduce 1/f noise when compared to traditional φ-OTDR, achieving long-term stability, and enabling precise monitoring of perturbations over extended periods. However, so far, a requirement for the fiber to be unperturbed during fiber calibration stage (i.e., MFDD reference matrix acquisition) limited its application in real-world scenarios, since perturbations occurring at this stage would lead to distortions in posterior measurements. In this paper a self-correction of the MFDD reference matrix is proposed. Since the MFDD reference matrix can itself be treated as a traditional CP-φ-OTDR measurement, perturbations occurring during the fiber calibration stage can be measured and compensated for in post-processing. This concept is experimentally validated. A MFDD-CP-φ-OTDR measurement was performed in two fiber positions: one where large perturbations were applied during the calibration stage (and later corrected and compensated for in post-processing) are another where the fiber calibration stage was performed without perturbations (used as ground-truth for baseline performance). The two measurements showed similar performances, both in fast (100Hz) and slow/static measurements. This validates that the method can ensure accurate reference matrices even under strong environmental noise, which enhances the reliability of MFDD-CP-φ-OTDR systems in practical field conditions.

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Published
2025-05-22
DOI
https://doi.org/10.1117/12.3061867
Primary Topic
Image and Signal Denoising Methods
Type
article
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article

Reference matrix self-correction for perturbation compensation in MFDD-DAS

Pedro J. Vidal-Moreno, Hugo Fidalgo Martins, Alfredo Rosado-Muñoz, Sonia Martín‐López et al.
Image and Signal Denoising Methods
article

Reference matrix self-correction for perturbation compensation in MFDD-DAS

Pedro J. Vidal-Moreno, Hugo Fidalgo Martins, Alfredo Rosado-Muñoz, Sonia Martín‐López, Laura Hernández-Martín, Marcos G. Barriopedro
article en

Abstract

Multi-Frequency Database Demodulation (MFDD) combined with chirped-pulse (CP) phase-sensitive OTDR (φ-OTDR) has been recently presented as a method for distributed acoustic sensing (DAS) systems that can reduce 1/f noise when compared to traditional φ-OTDR, achieving long-term stability, and enabling precise monitoring of perturbations over extended periods. However, so far, a requirement for the fiber to be unperturbed during fiber calibration stage (i.e., MFDD reference matrix acquisition) limited its application in real-world scenarios, since perturbations occurring at this stage would lead to distortions in posterior measurements. In this paper a self-correction of the MFDD reference matrix is proposed. Since the MFDD reference matrix can itself be treated as a traditional CP-φ-OTDR measurement, perturbations occurring during the fiber calibration stage can be measured and compensated for in post-processing. This concept is experimentally validated. A MFDD-CP-φ-OTDR measurement was performed in two fiber positions: one where large perturbations were applied during the calibration stage (and later corrected and compensated for in post-processing) are another where the fiber calibration stage was performed without perturbations (used as ground-truth for baseline performance). The two measurements showed similar performances, both in fast (100Hz) and slow/static measurements. This validates that the method can ensure accurate reference matrices even under strong environmental noise, which enhances the reliability of MFDD-CP-φ-OTDR systems in practical field conditions.

Universidad de Alcalá (ES), Instituto de Óptica "Daza de Valdés" (ES), Universidad Politécnica de Madrid (ES)
Openalex Percentile: Top 91%
Image and Signal Denoising Methods
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Reference matrix self-correction for perturbation compensation in MFDD-DAS — Pedro J. Vidal-Moreno, Hugo Fidalgo Martins, et al. · (2025) | TGRS Research Map | TGRS