Hardware-free low-frequency drift compensation method for interferometric fiber-optic vibration sensing

• Proposes a method leveraging the system’s intrinsic transmission delay to suppress low-frequency noise. • Compensates low-frequency drift without extra components. • Achieves 81.49 dB noise floor suppression at 10 mHz over 50 km SMF. • Enables simultaneous mHz–kHz detection via down sampling. • Outperforms wavelet and EMD in noise suppression and signal fidelity. Fiber-optic vibration sensors are crucial for detecting subtle disturbances in applications such as ocean seismic monitoring and structural health assessment. Among various configurations, interferometric fiber-optic sensors offer the advantages of long-range measurement, high dynamic range, and seamless integration into existing telecommunication networks. However, their performance is significantly constrained by laser frequency noise, particularly low-frequency drift, which degrades both sensitivity and signal-to-noise ratio (SNR). To address this issue, a Sampling Matched Integral Fitting Difference (SMIFD) scheme is proposed for low-frequency drift compensation in interferometric fiber-optic vibration sensing systems, leveraging intrinsic system properties and hardware component-free. By synchronizing the sampling rate with the fiber’s transmission delay, the randomly distributed low-frequency noise is transformed into phase drift with discernible time–frequency characteristics through integration. Subsequently, the laser frequency drift can be predicted and mitigated from the phase drift through polynomial fitting. The experimental demonstration shows that SMIFD achieves significant noise floor suppression of 81.49 dB at 10 mHz and a SNR enhancement of 27.02 dB at 200 mHz over a 50 km single-mode fiber link. Furthermore, the down-sampling strategy is used to overcome the sampling rate limitation imposed by the transmission delay, enabling a broadband detection from millihertz to kilohertz range. Experimental results confirm that our method achieves the measurement accuracy required for ocean monitoring applications, even in high-drift conditions, enabling precise detection of low-frequency activities.