基于平稳小波变换的飞行数据去噪方法  

Flight data denoising method based on stationary wavelet transform

作　　者：李正欣[1] 张凤鸣[1] 张晓丰[1] 费文 

机构地区：[1]空军工程大学工程学院,西安710038 [2]北京军区空军装备部,北京100061

出　　处：《计算机应用》2011年第10期2790-2792,2810,共4页journal of Computer Applications

摘　　要：为更有效地去除飞行数据中的噪声,分析了平稳小波变换的基本原理,将小波系数相关性与阈值收缩去噪方法相结合,提出一种基于系数相关性的改进阈值函数去噪方法。该方法采用平稳小波变换,先对小波系数进行相关性分析,而后使用改进的阈值函数对小波系数进行阈值处理,最后进行信号重构。实验结果表明:该方法不仅能够很好地保持信号的形状,而且信噪比较高、均方误差较小;在实际的飞行数据处理中能够获得较好的去噪效果。In order to get rid of the noise of flight data more effectively,based on discussing the principle of Stationary Wavelet Transform（SWT）,a new denoising method was proposed,which combined correlation of wavelet coefficient with wavelet shrinkage.Firstly,signals were decomposed by using SWT;secondly,wavelet coefficient was dealt with by using methods of coefficient correlation and wavelet shrinkage in sequence;at last,denoised signal was reconstructed through inverse wavelet transform.The results of experiments show that the proposed method can raise Signal-to-Noise Ratio（SNR）,decrease Mean Squared Error（MSE） and preserve the shape of signal;and it can be applied to flight data effectively.

关 键 词：飞行数据 多元时间序列 平稳小波变换 信号去噪 阈值函数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TN911.72[自动化与计算机技术—控制科学与工程]