基于高斯拟合的光纤型SPR信号的峰值检测算法

光纤型表面等离子共振光谱具有半峰宽较宽，共振峰不尖锐等特征，传统的针对棱镜型SPR光谱的峰值检测算法无法准确定位此类光谱的共振峰值。为了准确计算光纤型SPR光谱的共振波长，提出了一种基于信赖域算法的高斯拟合方法，在拟合的光谱曲线上利用一维搜索的方式确定峰值位置。通过对标准甘油光谱数据的处理，证明高斯拟合法能够适应光纤型SPR光谱的特征，波长计算准确。通过搭建的SPR系统，实验测量了不同浓度下蔗糖溶液的SPR光谱数据，并分别采用加权质心法，追踪质心法和该研究提出的高斯拟合法进行共振波长的计算。结果表明高斯拟合法能够有效提升分辨率，且运算速度较快，有利于工程集成。

Peak Detection Algorithm of Optical Fiber SPR Signal Based on the Gaussian Fitting

The spectrum of optical fiber surface plasmon resonance (SPR) shows the characteristics of wider full width at half‐maximum (FWHM ) and smaller peak value .The traditional peak detection algorithm cannot calculate the resonance wavelength of this kind of spectrum accurately .Therefore ,efficient methods to calculate the resonance wavelength are required .This paper presents a method to process the SPR signal based on the Gaussian fitting .Combined with the trust region algorithm to deter‐mine the Gaussian fitting function ,and then the resonance wavelength be calculated by line search method .Data processing of standard spectrum of glycerin with different concentration proves that this algorithm can adapt to optical fiber SPR spectrum characteristics ,and calculate resonance wavelength accurately .The experiment measures the SPR signals of sucrose under differ‐ent concentrations through the self‐building SPR measure system .By using the proposed method ,the weighted centroid method and the tracking centroid method to calculate the resonance wavelength ,the result shows that the Gaussian fitting method can ef ‐fectively improve resolution and have a short operation time which is conducive to engineering application .