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基于小波阈值算法的海杂波信号去噪
引用本文:王福友,刘刚,袁赣南.基于小波阈值算法的海杂波信号去噪[J].雷达与对抗,2009(2):21-26,59.
作者姓名:王福友  刘刚  袁赣南
作者单位:[1]南京电子技术研究所,南京210013 [2]哈尔滨工程大学自动化学院,哈尔滨150001
摘    要:为有效提取噪声背景下的海杂波信号,针对海杂波信号非线性非平稳的特点,提出基于小波阈值算法对实测海杂波数据去噪。在噪声水平未知条件下,提出基于噪声主要在高频段且能量较小、信号主要集中在低频段思想的噪声判断准则。为验证小波去噪效果,将该算法对含有噪声的海杂波实测数据进行去噪,采用均方差和降噪信号信噪比两项指标来衡量去噪效果,并与均值和中值等去噪方法对比,小波算法在这两项指标均优于其他算法;此外,实验结果还表明,db2小波在双曲线阈值函数和HeurSure阈值模式下优于其他小波去噪效果。

关 键 词:海杂波信号  非线性非平稳  小波阈值算法  噪声判断准则  去噪

Wavelet threshold-based sea clutter signal denoising
Affiliation:WANG Fu-you, LIU Gang , YUAN Gan-nan (1. Nanjing Research Institute of Electronics Technology, Nanjing 210013; 2. College of Automation, Harbin Engineering University, Harbin 150001 )
Abstract:Considering the nonlinearity and nonstationarity of the sea clutter, a denoising method for the real sea clutter data based on the wavelet threshold algorithm is presented to effectively extract the sea clutter signals under the noise background, and the noise estimation criterion with the unknown noise level is presented based on the basic idea that the noise is concentrated on the high frequency range with little energy but the signals on the low one. The method is used to verify the effect of the wavelet denoising via the denoised signal-to-noise ratio (DSNR) and mean square error ( MSE), and it outperforms the mean and median methods. Besides, the results show that the db2 wavelet with the HeurSure and Hyperbolic threshold function is superior to the other wavelets for denoising.
Keywords:sea clutter signal  nonlinearity and nonstationarity  wavelet threshold algorithm  noise estimation criterion  denoising
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