改进的Chirp信号LMMSE参数估计算法  

Improved linear minimum mean squares error estimation of the parameters of Chirp signals

作　　者：沈宙 张善从[2] Shen Zhou;Zhang Shancong(University of Chinese Academy of Sciences,Beijing 100094,China;Technology and Engineering Center for Space Utilization,Chinese Academy of Sciences,Beijing 100094,China)

机构地区：[1]中国科学院大学,北京100094 [2]中国科学院空间应用工程与技术中心,北京100094

出　　处：《电测与仪表》2020年第6期19-22,共4页Electrical Measurement & Instrumentation

摘　　要：线性调频信号(Chirp信号)的参数估计是信号处理中长期研究的一个问题,其最大似然估计算法已经被提出并且得到广泛应用。然而在许多实际应用中,通常已经知道了被估计参数的分布,因此可以使用贝叶斯估计器的方法。在文中,通过加入先验知识,给出了参数的线性最小均方误差(Linear Minimum Mean Squares Error:LMMSE)估计算法。与传统的最大似然估计算法相比,此方法有更好的性能。同时,文中基于两种线性相位模型实现了LMMSE估计算法,一种是传统的线性相位模型,另一种是最近提出的最佳线性相位模型。实验结果表明基于最佳线性相位模型的估计器具有更好的性能。Parameter estimation of Chirp signals has been studied for a long time.The maximum likelihood estimation algorithm has been proposed and applied widely.However,in many practical applications,we have known the distributions of the parameters to be estimated and the Bayes estimator can be used.In this paper,the linear minimum mean square error(LMMSE)estimation algorithm of the parameters is given by incorporating a priori knowledge.This method outperforms the traditional maximum likelihood estimator.Besides,the LMMSE estimation algorithm is realized based on two linear phase models.One is the traditional linear phase model and the other is the optimal linear phase model which is presented recently.The result shows that the estimator based on the optimal linear model has a better performance.

关 键 词：参数估计 线性调频信号 贝叶斯估计 最小均方误差估计 

分 类 号：TN951[电子电信—信号与信息处理]