Field experiment demonstrates accurate strain calibration against distributed acoustic sensing in optical cables, highlighting its viability as a long-range broadband strainmeter.
Microwave-frequency fiber interferometry (MFFI) is an implementation of integrated fiber-optic sensing (IFOS) that uses existing telecommunication cables to measure strain integrated over long distances. As such, it complements distributed acoustic sensing (DAS), which relies on weak Rayleigh backscattering rather than forward-propagating light, and the range for which is therefore typically limited to less than ∼100 km. Compared with DAS, however, MFFI signals remain poorly characterized in terms of signal content and broadband detection capability. To address this, we conducted a short-distance experiment in which a 15.3 km terrestrial–submarine cable on Kefalonia Island, Greece, was simultaneously instrumented with MFFI and DAS for two months in 2024. The aim of this study is to calibrate MFFI signals quantitatively against collocated DAS observations, thereby preparing the ground for future long-range deployments beyond the reach of DAS. We derive and experimentally verify a conversion model showing that MFFI signals can be approximated by the spatial mean of collocated DAS signals. Using this calibration, we characterize MFFI sensitivity across three frequency–source regimes: (1) in the ocean-wave band (0.1–0.4 Hz), MFFI amplitudes correlate with significant wave height; (2) in the earthquake band (1–12 Hz), waveform-coherence-based manual inspection resolves events down to ML≈1.7 at ∼13 km from the cable center; and (3) localized vehicle signals (1–12 Hz, affecting only short cable segments rather than the whole fiber) remain resolvable in the integrated record. What limits detection is therefore not instrument noise but an unresolved environmental background: roadside traffic and ocean-wave signals superpose along the whole cable and, unlike in DAS, cannot be separated spatially. Even so, MFFI recovers seismic phase and amplitude information consistent with the spatial DAS mean, supporting its use as a cost-effective broadband strainmeter.
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Wang et al. (2026) studied this question.
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