Fiber Bragg Gratings (FBGs) are among the most popular optical fiber sensors. FBGs are well suited for direct detection of\ntemperature and strain and can be functionalized for pressure, humidity, and refractive index sensing. Commercial setups for\nFBG interrogation are based on white-light sources and spectrometer detectors, which are capable of decoding the spectrum of an\nFBG array. Low-cost spectrometers record the spectrum on a coarse wavelength grid (typically 78ââ?¬â??156 pm), whereas wavelength\nshifts of 1 pm or lower are required by most of the applications. Several algorithms have been presented for detection of small\nwavelength shift, even with coarsewavelength sampling; most notably, the Karhunen-Loeve Transform(KLT) was demonstrated. In\nthis paper, an improved algorithm based on KLT is proposed, which is capable of further expanding the performances. Simulations\nshow that, reproducing a commercial spectrometer with 156 pm grid, the algorithm estimates wavelength shift with accuracy\nwell below 1 pm. In typical signal-to-noise ratio (SNR) conditions, the root mean square error is 22ââ?¬â??220 fm, while the accuracy\nis 0.22 pm, despite the coarse sampling. Results have been also validated through experimental characterization. The proposed\nmethod allows achieving exceptional accuracy in wavelength tracking, beating the picometer level resolution proposed in most\ncommercial and research software, and, due to fast operation (>5 kHz), is compatible also with structural health monitoring and\nacoustics.
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