本文選題：降噪　切入點(diǎn)：稀疏表示　出處：《聲學(xué)技術(shù)》2017年04期

【摘要】：為了對(duì)實(shí)時(shí)采集的水聲信號(hào)進(jìn)行數(shù)據(jù)壓縮的同時(shí)實(shí)現(xiàn)信號(hào)降噪,提出了一種動(dòng)態(tài)閾值正交匹配追蹤方法(Dynamic Threshold Orthogonal Matching Pursuit,DTOMP)。該方法將稀疏分解原理應(yīng)用于水聲信號(hào)的預(yù)處理,通過(guò)在正交匹配追蹤算法中引入閾值約束,并根據(jù)噪聲分布特性將其分為兩部分,用以控制預(yù)設(shè)置的參數(shù)。通過(guò)對(duì)加噪正弦信號(hào)、實(shí)測(cè)鯨魚(yú)叫聲和艦船輻射噪聲信號(hào)的降噪實(shí)驗(yàn),表明該方法能夠在對(duì)原始水聲信號(hào)進(jìn)行壓縮的同時(shí)提高信噪比,且在較寬的信噪比變化范圍內(nèi)比小波方法具有更好的降噪性能。
[Abstract]:In order to compress the data of underwater acoustic signals collected in real time and reduce the noise of signals, a dynamic threshold orthogonal matching tracking method is proposed. The sparse decomposition principle is applied to the pretreatment of underwater acoustic signals. By introducing the threshold constraint into the orthogonal matching tracking algorithm and dividing it into two parts according to the characteristics of the noise distribution, it is used to control the preset parameters. The experimental results of whale calls and ship radiated noise signals show that the proposed method can compress the original underwater acoustic signals and improve the signal-to-noise ratio (SNR) at the same time, and it has better noise reduction performance than the wavelet method in a wide range of signal-to-noise ratio (SNR) variations.
【作者單位】： 西北工業(yè)大學(xué)航海學(xué)院;
【分類(lèi)號(hào)】：TB56

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相關(guān)會(huì)議論文 前2條

1 李政;羅飛路;;基于匹配追蹤的超聲回波參數(shù)估計(jì)方法[A];2009中國(guó)儀器儀表與測(cè)控技術(shù)大會(huì)論文集[C];2009年

2 秦曉偉;郭建中;;匹配追蹤算法(MP)在超聲成像中的研究[A];第二屆西安-上海兩地聲學(xué)學(xué)術(shù)會(huì)議論文集[C];2011年

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