基于自适应方法在自然伽玛能谱的应用

Smoothing Technology of Gamma-ray Spectrometry Data Based on Matched Filtering

针对传统多项式拟合平滑法用于处理谱线容易造成谱线畸变的缺点,在维纳滤波器的基础上,采用自适应滤波器的原理,设计了自适应维纳滤波器,并将该方法用于对伽玛能谱数据进行处理。将该方法与多项式最小二乘法光滑去噪做定性分析和比较,表明该方法能比较好地降低自然伽玛能谱中的噪声。

Aimed at the weakness of traditional method on smoothing the gamma - ray spectrometry data, the method based on the wiener and adaptive filter hasd been proposed to solve the problem about denoising the spectrum and an adaptive wiener filter has been designed to process the gamma - ray spectrometry data. By means of qualitative analysis comparing the least - squares polynomial fitting method and this new method, it shows that adaptive wiener filter will be a better way to remove the noise in the gamma - ray spectrometry data.