本文關(guān)鍵詞：基于寬間距麥克風(fēng)陣列的多聲源測向方法研究　出處：《南京理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 寬間距麥克風(fēng)陣列 多聲源波達方向估計 聚合角度譜 空間混疊抑制 時頻稀疏

【摘要】：本課題依托國家自然科學(xué)基金(61171167,61401203),開展了對寬間距麥克風(fēng)陣列多聲源測向方法研究�；邴溈孙L(fēng)陣列的多聲源測向技術(shù)通過處理由陣列接收的混合聲頻信號來確定各個聲源的方位,在軍事和民用的多個領(lǐng)域有著廣泛應(yīng)用。例如在視頻會議中,利用該技術(shù)精確估計發(fā)言人所在方位可以對其語音進行增強并準(zhǔn)確控制攝像頭。通過接收和處理槍炮聲信號,還能實現(xiàn)敵方狙擊手探測定位以及戰(zhàn)場態(tài)勢檢測等功能。此外,隨著對聲源信號分析帶寬要求和空間分辨率要求的不斷提高,采用寬間距麥克風(fēng)陣列獲取更寬頻帶信號信息是有效控制實際聲測系統(tǒng)復(fù)雜度和成本的合理措施。因此對寬間距麥克風(fēng)陣列多聲源測向方法的研究將具有十分重要的意義。本文首先歸納總結(jié)了傳統(tǒng)的聲源測向方法。由于基于時延估計的波達方向估計技術(shù)具有計算量小、精確性高等優(yōu)勢,本文主要討論該領(lǐng)域最基礎(chǔ)問題之一的雙元麥克風(fēng)陣列時延估計技術(shù)。針對遠場多聲源模型,在分析比較傳統(tǒng)廣義互相關(guān)(GCC)法和退化分離估計技術(shù)(DUET)的特點及局限性基礎(chǔ)上重點對角度譜類方法開展研究,分別說明了基于最小方差無失真響應(yīng)(MVDR)和擴散噪聲模型(DNM)的兩種聚合角度譜,并對各自特點進行了分析比較。該類方法能夠在混響環(huán)境下實現(xiàn)多聲源測向,但是當(dāng)聲源信號存在波長之半小于麥克風(fēng)間距的高頻成分時,將會由于空間混疊出現(xiàn)相位卷繞模糊問題,限制了其在寬間距陣列中的應(yīng)用。針對上述問題,本文研究了一種新的聚合角度譜方法,采用聲源能量積累策略和恒虛警率檢測技術(shù),僅對頻域積累輸出中的高值分量進行幀間時域聚合處理,顯著降低了聚合角度譜中的空間混疊偽峰高度和數(shù)量。詳細闡述了該方法的原理及實現(xiàn)流程,并開展了大量仿真和外場實驗驗證。實驗結(jié)果表明,本文所述方法在應(yīng)用于寬間距陣列時能夠顯著抑制空間混疊的影響,有利于提高多聲源檢測和測向性能。
[Abstract]:This subject relies on the National Natural Science Foundation of China 61171167 (61401203). The multi-source direction-finding technology based on microphone array determines the azimuth of each sound source by processing the mixed audio signals received by the array. It has a wide range of applications in military and civilian fields, such as videoconferencing. Using this technique, the speaker's voice can be enhanced and the camera can be accurately controlled by accurately estimating the location of the speaker, and the sound signal of the gun can be received and processed. In addition, with the increasing requirement of bandwidth and spatial resolution for the analysis of sound source signal, the detection and location of enemy sniper and battlefield situation can be realized. It is a reasonable measure to control the complexity and cost of practical sound measurement system by using wide spacing microphone array to obtain wider band signal information. Therefore, the research on direction finding method of multi sound source with wide spacing microphone array will be very important. This paper first summarizes the traditional acoustic source direction finding methods. Due to the time delay estimation based on the direction of arrival estimation technology has a small amount of calculation. In this paper, one of the most basic problems in this field, the dual-element microphone array time delay estimation technology, aimed at the far-field multi-source model. Based on the analysis and comparison of the characteristics and limitations of the traditional generalized cross-correlation GCCs and the degenerate separation estimation techniques, this paper focuses on the study of angle spectrum methods. Two convergent angle spectra based on minimum variance distortion free response (MVDR) and diffusion noise model (DNM) are presented respectively. This method can realize multi-source direction finding in reverberation environment, but when the sound source signal has a high frequency component of half wavelength less than microphone spacing. Due to the phase winding ambiguity problem in spatial aliasing, its application in wide spaced array is limited. In view of the above problems, a new method of polymerizing angle spectrum is studied in this paper. Based on the acoustical source energy accumulation strategy and CFAR detection technique, only the high value components in the frequency domain accumulation output are processed by time domain aggregation. The height and the number of pseudo peaks of spatial aliasing in the polymerization angle spectrum are significantly reduced. The principle and implementation flow of this method are described in detail, and a large number of simulations and field experiments are carried out. The experimental results show that. The method proposed in this paper can significantly suppress the influence of spatial aliasing when it is applied to wide spacing arrays, and is helpful to improve the detection and direction finding performance of multi-sound sources.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN912.3

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本文編號：1428845