Virtual Vernier Enabled Remotely Tunable Fiber Sensors for Advanced Dynamic Field Detection

Fiber interferometric sensors often struggle to balance sensitivity, noise resilience, and adaptability. This work presents a computational interference modulation strategy that creates virtual Vernier effects using real-time spectral processing with digitally controlled free spectral range (FSR) mismatches, eliminating the need for extra hardware. Experimental validation with displacement sensing demonstrates that direct dip-tracking algorithms achieve picometer-level resolution across a wide 5 nm to 1 mm range and reduce noise by about 50% compared to standard Vernier methods. In acoustic sensing, the baseline sensitivity of a fiber-optic microphone (2.04 pm/Pa) is boosted 1,446× to 2.95 nm/Pa using the virtual Vernier approach, which also allows remote sensitivity tuning (3.46–6.79 nm/Pa) and reliably detects sub-Hz acoustic signals down to 0.5 Hz. For vibration detection, sensitivity at low frequencies is improved to 407× (from 15.69 pm/V to 6.40 nm/V), with consistent sub-Hz tracking and better SNR. By removing physical limitations, this approach enables flexible sensitivity upgrades for existing fiber sensors, supporting advanced applications in industrial metrology, biomedical diagnostics, and environmental monitoring, and positioning computational fiber interferometers as a powerful technology for future sensing systems.