摘要
为有效提取噪声背景下的海杂波信号,针对实际海杂波信号非线性非平稳的特点,提出基于EMD算法对实测海杂波数据去噪。对噪声水平未知条件下,EMD算法分解的哪些内蕴模式是信号部分难以有效界定的问题,提出基于噪声主要在高频段且能量较小、信号能量主要集中在低频段思想的噪声判断准则。为验证EMD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,采用信噪比和均方差两项指标衡量去噪效果,并与均值、中值、db2小波等去噪方法对比,EMD算法在这两项指标均优于其他算法,说明EMD算法对海杂波数据去噪是有效的。
In order to effectively extract the sea clutter signal within noisy background, a signal-filtering method based on empirical mode decomposition（EMD） is presented for sea clutter denoising in consideration that the real sea clutter is nonlinear and nonstationary. As to the intrinsic mode functions from EMD which belong to the signal can not be determined when 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 EMD denoising. The denoised signal to noise ratio（I）SNR） and mean square error（MSE） are employed to measure the efficiency of noise reduction. The EMD filtering outperforms the averaging, median, and db2 wavelet methods, so the EMD-based denoising for real-life sea clutter is effective.
出处
《雷达科学与技术》
2010年第2期177-182,187,共7页
Radar Science and Technology
关键词
海杂波信号
非线性非平稳
EMD算法
噪声判断准则
去噪
sea clutter signal
nonlinear and nonstationary
EMD method
noise judge criterion
denoising
