Haneef Shahna M, Yang Zhisheng, Thévenaz Luc, Venkitesh Deepa, Srinivasan Balaji
Opt Express. 2018 May 28;26(11):14661-14677. doi: 10.1364/OE.26.014661.
The performance of post-processing techniques carried out on the Brillouin gain spectrum to estimate the Brillouin frequency shift (BFS) in standard Brillouin distributed sensors is evaluated. Curve fitting methods with standard functions such as polynomial and Lorentzian, as well as correlation techniques such as Lorentzian Cross-correlation and Cross Reference Plot Analysis (CRPA), are considered for the analysis. The fitting procedures and key parameters for each technique are optimized, and the performance in terms of BFS uncertainty, BFS offset error and processing time is compared by numerical simulations and through controlled experiments. Such a quantitative comparison is performed in varying conditions including signal-to-noise ratio (SNR), frequency measurement step, and BGS truncation. It is demonstrated that the Lorentzian cross-correlation technique results in the largest BFS offset error due to truncation, while exhibiting the smallest BFS uncertainty and the shortest processing time. A novel approach is proposed to compensate such a BFS offset error, which enables the Lorentzian cross-correlation technique to completely outperform other fitting methods.
对在布里渊增益谱上进行的后处理技术在标准布里渊分布式传感器中估计布里渊频移（BFS）的性能进行了评估。分析中考虑了使用多项式和洛伦兹等标准函数的曲线拟合方法，以及洛伦兹互相关和交叉参考图分析（CRPA）等相关技术。对每种技术的拟合程序和关键参数进行了优化，并通过数值模拟和控制实验比较了在BFS不确定性、BFS偏移误差和处理时间方面的性能。在包括信噪比（SNR）、频率测量步长和BGS截断在内的不同条件下进行了这种定量比较。结果表明，由于截断，洛伦兹互相关技术导致最大的BFS偏移误差，同时表现出最小的BFS不确定性和最短的处理时间。提出了一种新颖的方法来补偿这种BFS偏移误差，这使得洛伦兹互相关技术能够完全优于其他拟合方法。
