Feature extraction of Brillouin scattering spectrum based on half-interval search frequency sweep method

In order to improve the real-time performance of Brillouin optical time-domain analysis (BOTDA) distributed optical fiber sensing system, this paper proposes an extraction method of Brillouin scattering spectrum based on half-interval search frequency sweep. This method shortens measurement time by reducing the frequency sweep range, and provides a simplified Brillouin gain spectrum. Cross-correlation of this spectrum with a standard Lorentz curve, then the ideal Lorentz line type near the peak of the convolution result is used for frequency shift feature extraction. And the estimated value of Brillouin frequency shift (BFS) can be calculated by the result of frequency shift feature extraction. A 15km Rayleigh BOTDA temperature sensing experiment is designed to verify the reliability of the method. The results show that this method avoids extension of measuring time caused by the complex iterative process, and reduces frequency sweep time. It has better real-time performance and measurement accuracy than traditional Lorenz curve fitting (LCF) which based on the Levenberg-Marquardt (LM) algorithm.