An improved fast Fourier transform demodulation algorithm based on high-fineness Fabry–Pérot sensors

To achieve low-noise demodulation of high-fineness Fabry-Perot (F-P) sensors. This paper uses Fast Fourier Transform (FFT) to preprocess the reflection spectrum of high-fineness F-P sensors, extract the phase changes at the eigen-peaks of different frequency components, and proposes a demodulation algorithm combined with the concept of averaging. Considering the influence of periodic variation of the spectrum of high-fineness F-P sensors, the average of two eigen-peaks is used to effectively reduce the noise interference in the signal demodulation process and improve the stability of the demodulation results. The simulation results show that the noise spectrum level can be lower, and the demodulation of the sensor uses a simple FFT for averaging, which provides a research basis for the multiplexing of high-fineness F-P sensors. This technique also provides an outstanding performance in engineering practice and holds great promise for application in large-scale array multiplexing in the oceans.