本文選題：麥克風(fēng)陣列　切入點(diǎn)：多源測(cè)向　出處：《南京理工大學(xué)》2014年碩士論文

【摘要】：基于麥克風(fēng)陣列的多聲源測(cè)向技術(shù)通過對(duì)麥克風(fēng)陣列接收的多聲源混合信號(hào)進(jìn)行處理,從而確定各個(gè)聲源的方位。它在很多領(lǐng)域都具有廣泛的應(yīng)用前景和實(shí)際意義,如在民用方面的視/音頻會(huì)議、語音識(shí)別及增強(qiáng)等領(lǐng)域中,常利用聲源測(cè)向技術(shù)精確估計(jì)出說話人位置來控制攝像頭,使其自動(dòng)對(duì)該位置的語音信號(hào)進(jìn)行增強(qiáng)。在軍事方面聲源測(cè)向技術(shù)被廣泛地應(yīng)用在飛機(jī),火炮、狙擊手探測(cè)等方面。因此,該技術(shù)成為了語音信號(hào)處理領(lǐng)域的研究熱點(diǎn)之一。 本課題針對(duì)基于麥克風(fēng)陣列多聲源測(cè)向問題展開研究,歸納總結(jié)并比較了傳統(tǒng)的幾類聲源測(cè)向方法。本文以典型的雙陣元麥克風(fēng)陣列為研究對(duì)象,針對(duì)遠(yuǎn)場(chǎng)多聲源模型,將基于語音信號(hào)時(shí)頻正交特性的退化分離估計(jì)技術(shù)(DUET)應(yīng)用于聲源信號(hào)測(cè)向。該算法利用了語音信號(hào)特有的時(shí)頻稀疏和短時(shí)正交特性(W-Disjoint Orthogonality, W-DO),基于此特性的時(shí)延估計(jì)算法計(jì)算量小,實(shí)現(xiàn)簡(jiǎn)單,僅用兩個(gè)麥克風(fēng)就可以實(shí)現(xiàn)多個(gè)聲源的方位測(cè)向。但是當(dāng)聲源存在波長(zhǎng)小于兩倍陣元間距的高頻成分時(shí),此類聲源測(cè)向方法將出現(xiàn)相位卷繞模糊問題,而陣元間距因物理尺寸限制也不可能無限縮小,因此限制了該類方法的實(shí)際應(yīng)用領(lǐng)域。針對(duì)上述問題,本文提出了一種基于迭代時(shí)頻掩蔽的寬間距麥克風(fēng)陣列多聲源測(cè)向方法,該方法通過迭代消去過程,顯著抑制了相位卷繞產(chǎn)生的影響。此外,結(jié)合基于能量的語音端點(diǎn)檢測(cè)技術(shù),本文進(jìn)一步給出了上述方法的實(shí)時(shí)處理算法步驟。針對(duì)上述方法,本文進(jìn)行了仿真實(shí)驗(yàn)和相關(guān)外場(chǎng)實(shí)驗(yàn),實(shí)驗(yàn)結(jié)果表明：針對(duì)寬間距麥克風(fēng)陣列多聲源測(cè)向,本文所述方法明顯優(yōu)于常規(guī)DUET類方法,具有一定的實(shí)際應(yīng)用價(jià)值。
[Abstract]:Multi-sound source direction-finding technology based on microphone array processes the mixed signals received by microphone array to determine the orientation of each sound source.It has a wide application prospect and practical significance in many fields, such as video / audio conference, speech recognition and enhancement in the civilian field, it often uses the sound source direction finding technology to accurately estimate the speaker's position to control the camera.Make it automatically enhance the speech signal at this position.Sound source direction finding technology is widely used in aircraft, artillery, sniper detection and so on.Therefore, this technology has become one of the research hotspots in the field of speech signal processing.This paper focuses on the research of multi-source direction finding based on microphone array, and summarizes and compares several traditional sound source direction finding methods.In this paper, a typical dual-array microphone array is studied. For the far-field multi-source model, the degenerate separation estimation technique based on the time-frequency orthogonality of speech signal is applied to the direction finding of the sound source signal.This algorithm utilizes the time-frequency sparse and short-time orthogonal characteristic of speech signal, W-Disjoint Orthogonality (W-DOA). The time delay estimation algorithm based on this characteristic has the advantages of small computation and simple implementation, and it can realize the azimuth direction finding of multiple sound sources with only two microphones.However, when the sound source has a high frequency component whose wavelength is less than two times the spacing of the array element, the phase winding ambiguity will occur in this method, and the distance between the elements can not be reduced indefinitely because of the limitation of the physical size.Therefore, the practical application field of this kind of method is limited.In order to solve the above problems, an iterative time-frequency masking method for direction finding of multi-source microphone arrays with wide spacing is proposed. The effect of phase winding is significantly suppressed by iterative elimination process.In addition, combined with the energy-based speech endpoint detection technology, this paper further gives the real-time processing algorithm steps of the above method.In view of the above methods, the simulation experiments and related field experiments are carried out in this paper. The experimental results show that the method presented in this paper is obviously superior to the conventional DUET method and has certain practical application value for the wide spacing microphone array multi-sound source direction finding.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN912.3

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本文編號(hào)：1728903