圓形麥克風陣列(CMA)相較於球型麥克風陣列(SMA)而言，運算量較少，由於生場定位的問題水平角比仰角來的重要的許多，以一般的應用與情境來說應用的較為廣泛。但是真正的圓形麥克風陣列並不能進行仰角的定位，對仰角不敏感，但是也可以做為空間中三維聲場的限制。從波束成型可以發現在仰角高於60度以及俯角低於60度，CMA的定位效果不是很明顯。本篇論文將提出2.5維麥克風陣列(2.5-D CMA) 將一個對數間距的線性陣列垂直放置在一個未障板圓形麥克風陣列的中心點上。在定位的部分，將會使用延遲總和演算法(DAS)分別應用在對數間距的線性陣列與未障板圓形麥克風陣列來找出聲源的方位。至於在聲源分離的部分將使用提可諾夫正規化(TIKR)與感知壓縮(CS)來進行聲源分離。經由提可諾夫正規化與感知壓縮演算法分離出來的語音訊號將透過正規化最小均方演算法(NLMS)與內部迭代法(IIT)來提升語音訊號的品質。至於硬體部分的架設，未障板圓形麥克風陣列將會使用三維印刷技術製造，上面將有24個微機電系統麥克風均勻散佈在圓環上，而對數間距的線性陣列則是使用壓克力製造而成，將會有8個微機電系統麥克風分布在上面。分離之後的音訊將會使用主觀與客觀的標準來進行判斷。客觀判斷將使用語音質量感性評估(PESQ)來當作評斷準則，主觀的聆聽測試也會用來當作評估的標準。

Circular microphone arrays (CMA) are preferred over more complex spherical microphone arrays (SMA) in the context of some audio applications because azimuthal angles of spatial sound are considered more important than the elevation angles in those scenarios. However, the fact that CMA does not resolve the elevation angle well can be a limitation for some applications which involves 3-dimensional sound fields. But this can also be a limitation in spatial audio rendering. Sources with elevation less than 60 degrees can be localized precisely respectively. This paper proposes a 2.5-dimensional (2.5-D) CMA that consists of an unbaffled CMA and a vertical logarithmic-spacing linear array on the top. In the localization stage, two delay-and-sum (DAS) beamformers are applied to the circular array and the linear array, respectively. The product of the identified angular patterns yields the direction of arrival (DOA). In the separation stage, Tikhonov Regularization (TIKR) and Compressive Sensing (CS) are employed to extract the source signal amplitudes from the output signals from two arrays. The extracted signals are further processed by Normalized Least-Mean-Square (NLMS) algorithm with Internal Iteration (IIT) Algorithm respectively in order to produce the source signal with improved quality. To validate the 2.5-D CMA experimentally, a three-dimensionally printed circular array comprised of a 24 micro-electro-mechanical-system (MEMS) microphone circular array and an 8- MEMS microphone logarithmic-spacing linear array is constructed for localization and separation for sound sources. Objective Perceptual Evaluation of Speech Quality (PESQ) test and a subjective listening test are undertaken in performance evaluation. The experimental results demonstrate better separation quality achieved by the CS combined with NLMS method than by the TIKR combined with NLMS method.

摘 要 4
ABSTRACT 6
誌 謝 8
Chapter 1 11
INTRODUCTION 11
Chapter 2 14
FORMULATIONS OF 14
CIRCULAR AND LINEAR 14
ARRAY 14
2.1 Circular Microphone Array 15
2.2 Logarithmic-Spacing Linear Array 17
Chapter 3 22
LOCALIZATION OF ACOUSTIC SOURCES 22
3.1 Delay-and-Sum Beamformer 23
3.2 Localization Using the 2.5-D Array 23
3.3 Localization Using the Full 3-D Array 25
Chapter 4 29
SEPARATION OF SOURCE SIGNALS 29
4.1 Array Signal Extraction 30
4.2 Output Correlator for the 2.5-D Array 33
Chapter 5 36
NUMERICAL SIMULATION AND EXPERIMENTAL VALIDATION 36
5.1 Two-Sources Example 37
5.2 Three-Sources Example 40
Chapter 6 57
CONCLUSION 57
APPENDIX 64

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