小波阈值去噪在尾流散射光信号处理中的应用  

Application of wavelet threshold de-noising in scattering optical wake flow signal processing

作　　者：万俊[1] 张晓晖[1] 饶炯辉[1] 

机构地区：[1]海军工程大学兵器工程系,武汉430033

出　　处：《激光技术》2011年第4期468-471,共4页Laser Technology

摘　　要：为了从噪声背景中有效地提取舰船尾流后向散射光信号,采用4阶Daubechies小波对采集的信号进行了1维离散小波变换,将主要包含目标船后向散射光信号的低频部分和主要包含噪声的高频部分区别开来,使用阈值函数进行小波系数处理。在小波软硬阈值去噪方法的基础上,提出了一种新的阈值函数。该阈值函数克服了硬阈值函数值不连续的问题和软阈值函数存在恒定偏差的问题,同时引进了度量数据分布稀疏性的熵值作为阈值函数的参量。结果表明,新的阈值函数不仅滤除了原信号中高频部分包含的噪声,还弥补了软硬阈值函数的不足,收到了良好的效果。For effectively detecting the backscattering optical wake flow signal from the noise, the collected original signal was transferred into one dimension discrete wavelets based on four Daubechies wavelet decomposition （db4WD） so that the low frequency term, indicating the backscattered signal from the shake waves, was distinguished from the high frequency terms, indicating noise. Then, the wavelet coefficients were obtained based on the threshold function. A new threshold function was put forward on the basis of wavelet soft and hard threshold de-noising method with entropies indicating the sparsity distribution of the original signal data. The new function can not only overcome discontinuity disadvantage of the hard threshold function, but also solve constant deviation in the soft threshold function. The new threshold function can effectively eliminate noise and overcome the disadvantage of soft and hard threshold function so that good results can be obtained.

关 键 词：散射 舰船尾流探测 小波变换 熵 

分 类 号：TN911.72[电子电信—通信与信息系统]