Abstract

Fiber optic interferometric (FOI) sensors are widely recognized for their high sensitivity, design flexibility, and multiplexing capabilities, making them ideal for applications ranging from structural health monitoring to biomedical diagnostics. However, conventional optical-domain interrogation techniques are often limited by the performance constraints of spectrometers. In this work, we present a radiofrequency (RF)-interferometric optical interrogation (RIOI) method for FOI sensors. This approach leverages microwave photonic (MWP) processing to encode the optical interference phase into an RF signal, which is then combined with a reference RF signal to produce a microwave-domain interferogram. By tracking spectral shifts in the RF domain, RIOI achieves high sensitivity and resolution while preserving the rich information content of traditional MWP filtering. Experimental results demonstrate the effectiveness of the method in strain sensing using a fiber in-line Fabry–Perot interferometer (FPI), achieving a strain sensitivity of 1.6961 kHz/με and a strain resolution down to 0.05 με. The RIOI scheme further supports multiplexing of multiple FPIs with distinct or similar cavity lengths, showing low crosstalk through joint frequency-time domain analysis. Moreover, this approach is compatible with intensity-modulation-based FOI sensors and offers tunable sensitivity. By combining the precision of optical interferometry with the robustness and scalability of RF signal processing, this hybrid RF–optical interrogation strategy provides a versatile and high-performance platform for next-generation fiber optic sensing. © 2026 Chinese Laser Press

Department(s)

Electrical and Computer Engineering

Publication Status

Open Access

International Standard Serial Number (ISSN)

2327-9125

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2026 Optica Publishing Group, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Publication Date

15 Apr 2026

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