A high accurate fitting algorithm for Brillouin scattering spectrum of distributed sensing systems based on LSSVM networks

Strain and temperature are the key measurement parameters in a distributed optical fiber sensing system based on Brillouin scattering, which may be determined by analyzing the Brillouin center frequency shift. In order to accurately extract the features of the Brillouin scattering spectrum of a distributed sensing system, we propose a high accurate fitting algorithm using differential evolution (DE) algorithm to optimize the least squares support vector machine (LSSVM) algorithm, and compare it with traditional Levenberg-Marquardt (LM) and the five times polynomial curve algorithm. The results show that the DE-LSSVM algorithm has higher fitting degree and smaller frequency shift error for different line widths, signal-to-noise ratio and linear weight ratio. Therefore, this algorithm can effectively improve the accuracy of frequency shift parameters in distributed optical fiber sensing system based on Brillouin scattering.