Selection of spectrum model in estimation of Brillouin frequency shift for distributed optical fiber sensor

摘要： To improve real-time performance in distributed optical ?ber sensor, the in?uence of Brillouin spectrum models on performance in estimation of Brillouin frequency shift (BFS) is systematically investigated. First, the related Brillouin spectrum models, objective functions, optimization algorithms and convergence criterion in estimation of BFS are introduced. The BFS estimation algorithms based on the Lorentzian, Gaussian, pseudo-Voigt and Voigt models are written in MATLAB. The algorithms are used to estimate BFS for numerically generated Brillouin spectra with di?erent values of SNR (Signal to Noise Ratio) and measured Brillouin spectra with di?erent values of pulse width and average time. The results reveal that regardless of the simpli?ed Lorentzian and Gaussian models or more accurate pseudo-Voigt and Voigt model-based algorithms used, the estimated BFS between di?erent algorithms is quite similar. However, the ?tting error of the simpli?ed model-based algorithms is larger than that of the more accurate model-based algorithms especially for the cases with high value of SNR. The computational burden of the former is less than that of the latter. The Voigt model-based algorithm requires the most computational e?ort. If the nonlinear least-square ?t method is used, the selection of spectrum model has no big in?uence on the accuracy in the estimated BFS. Therefore, the algorithm based on simpli?ed Lorentzian and Gaussian models should be selected in BFS estimation. Thus, not only high accuracy in BFS estimation is ensured, but also the computation time can, at best, decrease to one-tenth of the maximum value.