Virtual Vernier enabled remotely tunable fiber sensors for advanced dynamic field detection

Area of Science:

• Optics and Photonics
• Sensor Technology
• Signal Processing

Background:

• Fiber interferometric sensors face challenges in balancing sensitivity, noise resilience, and adaptability.
• Existing Vernier methods often require additional hardware, limiting flexibility.

Purpose of the Study:

• To develop a computational interference modulation strategy for enhancing fiber optic sensor performance.
• To eliminate the need for extra hardware by creating virtual Vernier effects.
• To demonstrate improved sensitivity, noise reduction, and adaptability in various sensing applications.

Main Methods:

• Implemented a computational interference modulation strategy using real-time spectral processing.
• Introduced digitally controlled free spectral range (FSR) mismatches to create virtual Vernier effects.
• Validated the approach using direct dip-tracking algorithms for displacement, acoustic, and vibration sensing.

Main Results:

• Achieved picometer-level resolution in displacement sensing over a wide range (5 nm to 1 mm) with ~50% noise reduction.
• Boosted fiber-optic microphone sensitivity by 1,446× (to 2.95 nm/Pa) and enabled remote sensitivity tuning.
• Improved low-frequency vibration sensitivity by 407× (to 6.40 nm/V) with reliable sub-Hz tracking and better SNR.
• Demonstrated detection of sub-Hz acoustic signals down to 0.5 Hz.

Conclusions:

• The computational virtual Vernier approach overcomes physical limitations of traditional fiber sensors.
• This method offers flexible sensitivity upgrades for existing fiber sensors, enabling advanced applications.
• Positions computational fiber interferometers as a key technology for future sensing systems in metrology, diagnostics, and environmental monitoring.