本文關(guān)鍵詞： 差分麥克風(fēng)陣列 聲強(qiáng)估計(jì) 時(shí)頻稀疏性 模糊聚類 聲源定位　出處：《南京航空航天大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：麥克風(fēng)陣列聲源定位一直是語(yǔ)音信號(hào)處理領(lǐng)域研究的熱點(diǎn)之一。經(jīng)典的聲源定位方法在小尺寸麥克風(fēng)陣列條件下的性能變差,精度無法滿足實(shí)際需要。因此,如何有效實(shí)現(xiàn)小尺寸陣列和混響噪聲環(huán)境下的聲源定位是麥克風(fēng)陣列處理領(lǐng)域中有待進(jìn)一步解決的關(guān)鍵問題。而基于差分麥克風(fēng)陣列的聲強(qiáng)估計(jì)方法為實(shí)現(xiàn)小尺寸陣列條件下的聲源定位提供了一條重要技術(shù)途徑。本文以差分麥克風(fēng)陣列為研究對(duì)象,以聲強(qiáng)估計(jì)作為主要定位手段,從單聲源和多聲源兩個(gè)角度進(jìn)行討論,并在此基礎(chǔ)上對(duì)基本方法進(jìn)行改進(jìn),從而實(shí)現(xiàn)聲源方位的準(zhǔn)確定位。具體的工作如下:首先介紹了差分麥克風(fēng)陣列定位的基本理論,然后詳細(xì)介紹了基于聲強(qiáng)估計(jì)、基于時(shí)延估計(jì)和基于可控波束形成的聲源定位方法的基本原理,并對(duì)其性能進(jìn)行仿真分析和比較。結(jié)果表明,基于聲強(qiáng)估計(jì)的聲源定位方法要優(yōu)于其他兩種方法,為接下來提出的算法奠定了基礎(chǔ)。針對(duì)聲強(qiáng)估計(jì)方法在高混響下性能變差的缺陷,本文結(jié)合局部標(biāo)準(zhǔn)差和瞬時(shí)方位估計(jì)值之間的關(guān)系提出了基于局部標(biāo)準(zhǔn)差加權(quán)的方法。仿真結(jié)果表明,此方法有一定的效果,但是改進(jìn)效果并不明顯。于是,本文提出了基于二次門限時(shí)頻掩蔽的定位方法。該方法從時(shí)頻域角度進(jìn)行了改進(jìn),定位精度得到提升。此外,本文還從空域角度進(jìn)行了算法改進(jìn),提出了基于波束指向性加權(quán)的方法,初步結(jié)果表明,此方法有效地提高了聲源定位的性能。最后,本文結(jié)合時(shí)頻域和空域改進(jìn)方法的優(yōu)點(diǎn),提出了基于時(shí)頻空域聯(lián)合處理的方法,仿真和實(shí)測(cè)數(shù)據(jù)結(jié)果表明,該方法要優(yōu)于只在時(shí)頻域或空域處理的方法。本文還對(duì)多聲源的聲強(qiáng)估計(jì)聲源定位方法進(jìn)行研究,分析了現(xiàn)有的直方圖方法的性能,提出了基于時(shí)頻掩蔽和模糊聚類分析的多聲源定位方法。從仿真結(jié)果和實(shí)驗(yàn)數(shù)據(jù)分析表明,本文提出的方法要優(yōu)于直方圖方法。
[Abstract]:Microphone array sound source localization has been one of the hotspots in the field of speech signal processing. The performance of the classical sound source localization method under the condition of small microphone array becomes worse, and the accuracy can not meet the actual needs. How to effectively realize sound source location in the environment of small array and reverberation noise is a key problem to be solved in the field of microphone array processing. The method of sound intensity estimation based on differential microphone array is to realize small scale. The sound source location under the condition of inch array provides an important technical approach. In this paper, the differential microphone array is taken as the research object. The sound intensity estimation is used as the main localization method, and the basic method is improved from the two angles of single sound source and multi sound source. The main work is as follows: firstly, the basic theory of differential microphone array positioning is introduced, and then the sound intensity estimation is introduced in detail. The principle of acoustic source location based on time-delay estimation and controllable beamforming is analyzed and compared. The results show that the sound source location method based on sound intensity estimation is superior to the other two methods. For the defects of the sound intensity estimation method under high reverberation, Based on the relation between local standard deviation and instantaneous azimuth estimation, a weighted method based on local standard deviation is proposed in this paper. The simulation results show that the method has some effect, but the improvement effect is not obvious. In this paper, a new location method based on quadratic threshold time-frequency masking is proposed. This method is improved from the angle of time-frequency domain, and the accuracy of location is improved. In addition, the algorithm is improved from the perspective of spatial domain. A beam-directivity weighted method is proposed. The preliminary results show that the proposed method can effectively improve the performance of sound source location. Finally, this paper combines the advantages of time-frequency domain and spatial domain improved methods. A method based on joint processing in time-frequency space domain is proposed. The simulation and measured data show that this method is better than that only in time-frequency domain or spatial domain. The performance of the existing histogram method is analyzed, and a multi-sound source location method based on time-frequency masking and fuzzy clustering analysis is proposed. The simulation results and experimental data show that the proposed method is better than the histogram method.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TN912.3

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