摘要
本文提出一种基于最小二乘线性曲线拟合的背景噪声提取方法,采用最小二乘线性曲线拟合算法对频段内各个频点对应的电平数据进行处理,提取样本的斜率特征值,通过比较特征值与设定的信号判定门限,实现信噪分离,将信号频点值对应的电平值替换为邻近噪声频点对应的电平值,从而准确获取该频段的背景噪声。
This paper proposes a method of ackground noise extraction based on least-squares linear curve fitting.The least squares linear curve fitting algorithm is used to process the corresponding level data of each frequency point in the frequency domain and extract the sample's slope eigenvalues.Compare the eigenvalues with the thresholds to achieve signal-to-noise separation,and the level values corresponding to the signal frequency point values are replaced with the level values corresponding to the adjacent noise frequency points,so that the background noise of the frequency domain is accurately obtained.
作者
徐国强
彭涛
王孟
杨文翰
Xu Guoqiang;Peng Tao;Wang Meng;Yang Wenhan(Urumqi Station of The State Radio Monitoring Center,Urumqi,830054;The State Radio Monitoring Center,Beijing,100037)
出处
《数字通信世界》
2018年第11期70-74,共5页
Digital Communication World
关键词
最小二乘线性曲线拟合
背景噪声提取
斜率特征值
least squares linear curve fitting
background noise extraction
slope eigenvalue
