Processing Optical Fiber Sensing Signals with Compressed Sensing under special working conditions

The environment of underground pipe gallery is complicated and the noise interference is large in the actual engineering application environment, which makes peak detection difficult. A processing method based on the compressed sensing algorithm which suitable for fiber Bragg grating sensor signal on this environment is proposed by analyzing multiple observation matrices, the sparsity K and the number of atoms m selected in each iteration, which can be improve the signal reconstruction accuracy and fidelity. The simulation results show that, the Gaussian random observation matrix can make the highest sensor signal reconstruction accuracy, and it can retain the fidelity and have the least processing time when K=20 and m=2.