Fiber sensing using UFWT-lasers and sparse acquisition

We propose a sparse acquisition technique for fiber Bragg grating (FBG) sensors with subsequent sparse reconstruction and provide an analytical model for the received sensing signal. High sampling rates require expensive hardware components such as A/D converters or filters which are replaced by a compressive sensing scheme to abate the sampling rate far below Nyquist which may also lower the system costs. Moreover, storage requirements are strongly reduced. Our proposed scheme exploits the characteristics and sparse structure of the reflected signal for which a detailed model is presented.