Adaptive filter-based interrogation of high-sensitivity fiber optic Fabry-Perot interferometry sensors

• We introduce a novel interrogation algorithm for EFPI sensors, based on adaptive filtering.
• This technique improves detection accuracy and resilience to low signal-to-noise (SNR), at no computational expense.
• Pressure accuracy of 6.1 Pa is achieved, improving 8 times over standard tracking and 22 times over commercial device.
• We demonstrate that accuracy is ∝SNR1/2 in lieu of “standard” ∝SNR.

A novel method for interrogation of fiber-optic Fabry-Perot interferometric (FPI) sensors arranged in a white-light setup is presented. The proposed approach is based on a recursive least square (RLS) adaptive filtering to estimate the length of the Fabry-Perot cavity. Applied to an extrinsic FPI sensor with 1.6 nm/kPa sensitivity, the interrogation method achieves pressure accuracy of 6.1 Pa (0.045 mmHg), with an improvement of 8.7 times over standard Q-point tracking method at no computational expense. The RLS-based algorithm also exhibits better resilience to low signal-to-noise ratio (SNR) conditions, achieving 0.87 mmHg accuracy for SNR = −5.0 dB. The proposed approach finds its best application in medical pressure sensors, for sub-mmHg in vivo pressure detection, and is based on a biocompatible FPI design.