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。
In order to effectively extract the sea clutter signal within noisy background,a signal-filtering method based on Wavelet threshold（VT） is presented for sea clutter denoising considering the real sea clutter is nonlinear and nonstationary.As to the noise-level is unknown,this paper presents a noise judge criterion based on the basic idea that the noise is concentrated on high-frequency ones and contains little energy,while the energy of signal is mainly concentrated on the low frequency ones.The noisy real-life sea clutter dataset is used to test the validity of VT denoising,denoised signal-to-noise ratio（DSNR） and mean square error（MSE） are employed to measure the efficiency of noise reduction,and the EMD filtering outperforms averaging,median.Besides,db2 wavelet with HeurSure threshold and Hyperbolic thresholding function is better than the other wavelets for denoising.
出处
《海洋测绘》
2010年第4期19-22,共4页
Hydrographic Surveying and Charting
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
sea clutter signal
nonlinear and nonstationary
wavelet threshold
noise judge criterion
denoising
