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A scheme of high-speed Brillouin Optical Time Domain Reflectometry (BOTDR) based on frequency- agile and compressed sensing is proposed and experimentally validated, using an adaptive sparse basis for the data obtained by the principal component analysis algorithm to achieve a sparse representation of the Brillouin spectrum. Then, using random frequency sampling and orthogonal matching pursuit algorithm, the reconstruction is successfully implemented. In the experiments, a conventional high-speed BOTDR mapping Brillouin Gain Spectrum (BGS) is used, where the frequency step and span are 4 MHz and 500 MHz, respectively. 37 random frequency samples of BGS are successfully recovered using compressed sensing technique, and the number of samples is only 30% of the full data. The compressed sensing technique can improve the sensing performance of conventional fast BOTDR at lower sampling frequencies, including a 3.3-fold increase in sampling rate or a 70% reduction in data storage.
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