线型优化最大熵光谱估计方法中自回归模型两种求解方法的比较  

Comparison of Two Methods to Solve AR Model Parameters of Line Shape Optimized Maximum Entropy Spectral Estimation

作　　者：高晓峰[1] 徐之海[1] 

机构地区：[1]浙江大学现代光学仪器国家重点实验室,浙江杭州310027

出　　处：《光谱学与光谱分析》2008年第11期2717-2720,共4页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(60577047);国家"863"计划项目(863-2006AA122107)资助

摘　　要：在光谱分辨率增强技术中,线型优化最大熵谱估计方法LOMEE(line shape optimized maximum en-tropy spectral estimation)是指通过傅里叶自退卷积技术消除光谱谱线线型对干涉图的影响,而后对干涉图进行自回归参数建模,求出自回归模型系数,代入光谱估计公式得到光谱图。文章采用了两种方法:修正协方差法MCOV(modified covariance method))和伯格法(Burg method)求解线型优化最大熵谱估计方法中的自回归模型系数,通过仿真试验,将阶次、信噪比对估计光谱的影响做了详尽的比较。研究结果表明,在线型优化最大熵谱估计方法中,用修正协方差法求解自回归模型系数要优于伯格法。Line shape optimized maximum entropy spectral estimation（LOMEE） is to remove the influence resulting from line shape by Fourier self-deconvolution and to model interferogram data in order to substitute AR model parameters for the spectral estimator.The proper calculation of AR model parameters in LOMEE is very important to the quality of recovered spectrum.Modified covariance method（MCOV） and Burg method were used to solve AR model parameters under different noise level.The simulation results of recovered spectrum were acquired with the two methods.The influences of AR order and signal-to-noise ratio on the simulation were compared.It is shown that MCOV is more excellent than Burg in LOMEE.

关 键 词：傅里叶自退卷积 自回归模型 光谱估计 阶次 信噪比 

分 类 号：TH744[机械工程—光学工程]