摘要
为了对实时采集的水声信号进行数据压缩的同时实现信号降噪,提出了一种动态阈值正交匹配追踪方法(Dynamic Threshold Orthogonal Matching Pursuit,DTOMP)。该方法将稀疏分解原理应用于水声信号的预处理,通过在正交匹配追踪算法中引入阈值约束,并根据噪声分布特性将其分为两部分,用以控制预设置的参数。通过对加噪正弦信号、实测鲸鱼叫声和舰船辐射噪声信号的降噪实验,表明该方法能够在对原始水声信号进行压缩的同时提高信噪比,且在较宽的信噪比变化范围内比小波方法具有更好的降噪性能。
In order to achieve data compression and denoising of realtime collected underwater acoustic signal, this paper presents a dynamic threshold orthogonal matching pursuit（DTOMP） method. This method uses sparse representation for underwater signal pre-processing by applying threshold to greedy algorithm, meanwhile divides noise into two parts according to its characteristics to control preset parameters. Experimental researches on noise reduction of sinusoidal signal plus Gaussian noise, whale blows and ship radiated noise signal indicate that this method could improve the SNR and meanwhile compress original signal. Moreover, this method has better performance over wavelet denoising in wider dynamic range of SNR.
出处
《声学技术》
CSCD
北大核心
2017年第4期378-382,共5页
Technical Acoustics
关键词
降噪
稀疏表示
动态阈值
正交匹配追踪
de-noising
sparse representation
dynamic threshold
orthogonal matching pursuit
