基于小波变换的卡尔曼滤波法在ICP-AES中的应用

在ICP－AES中，卡尔曼滤波是一种有效的光谱干扰校正方法，它在强背景、谱线重叠严重的情况下，仍可得到很好的分析结果；并且有比传统分析线法在纯组分试样条件下更低的检出限。然而，噪声的存在影响了卡尔曼滤波的准确度。小波变换因其多分辨分析的特性，近年来被用于分析信号的去噪，而且该方法简单、快速，是一种很有效的去噪方法。本文首先用仿真数据研究了噪声对卡尔曼滤波法的影响；其次，将小波变换引入卡尔曼滤波法，提出了基于小波变换的卡尔曼滤波法，仿真实验结果表明，该方法能有效提高卡尔曼滤波法的分析准确度。

Application of Kalman Filtering Based on Wavelet Transform in ICP-AES

Kalman filtering is a recursive algorithm, which has been proposed as an attractive alternative to correct overlapping interferences in ICP AES. However, the noise in ICP AES contaminates the signal arising from the analyte and hence limits the accuracy of kalman filtering. Wavelet transform is a powerful technique in signal denoising due to its multi resolution characteristics. In this paper, first, the effect of noise on kalman filtering is discussed. Then we apply the wavelet transform based soft thresholding as the pre processing of kalman filtering. The simulation results show that the kalman filtering based on wavelet transform can effectively reduce the noise and increase the accuracy of the analysis.