本研究介紹整合式麥克風陣列及喇叭陣列應用於分析房間響應和合成空間聲場。此陣列系統的運作包含兩個階段：在第一個階段，利用麥克風陣列分析以及將迴響聲場「編碼」，將聲場簡化為僅由聲源方向以及訊號兩個物理量來表示，此麥克風陣列是利用MPDR和CS兩種波束成型的方法來測定平面波的方向。對於聲源的分離使用TIKR，可以在聲源數量符合稀少性的情況將聲源編碼。另一方面，對於一個真實房間、聲源數量不符合稀少性的情況時，我們能用麥克風陣列在房間中收到的聲場，編碼成許多等間距角度的訊號。也是本研究的重點。
在第二個階段，利用喇叭陣列可以在第一階段中所獲得的聲場資訊「解碼」以及重現，其中包含聲源方位、訊號。在這個階段我們透過在重建範圍內設置大量的假想控制點，來對欲重建的聲場做取樣，進而由這些控制點來反推喇叭訊號。而實際在一個真實房間中重現聲場的時候，會使用兩個方法做比較，一個方法是使用自由空間聲場反算，另一個方法則是使用房間環境反算。
實驗結果顯示，在真實房間中，使用房間環境反算的訊號在喇叭範圍內中可以重現目標聲波且誤差較小，在定位及消除迴響的效果上有明顯地提升，相對地在音質上會有所損失。而使用自由空間聲場反算的訊號因受到房間的反射，在定位及消除迴響的效果上較差。

A unified framework is proposed for analysis and synthesis of spatial reverberant sound fields. In sound field analysis (SFA), a 24-element circular microphone array (CMA) is utilized to encode the sound field based on plane-wave decomposition, whereas in sound field synthesis (SFS) a 32-element rectangular loudspeaker array is employed to decode the encoded sound field using pressure matching technique. Depending on the sparsity of the sound sources, the SFA stage can be implemented in two ways. For the sparse-source scenario, a two-stage algorithm is utilized to estimate the source bearings using the minimum power distortionless response (MPDR) and the associated amplitudes of plane waves using the Tikhonov regularization (TIKR) algorithm. Alternatively, a one-stage algorithm based on compressive sensing (CS) algorithm can be used. For the nonsparse-source scenario, a one-stage TIKR algorithm is utilized to solve for the amplitudes for plane-wave components uniformly distributed in the angular domain. The SFA technique for the nonsparse source scenario is also useful in establishing the room response model, as required in the pressure matching step of the SFS phase. The integrated acoustic array system is validated with localization and listening tests.

摘要 i
ABSTRACT ii
誌謝 iii
CONTENTS iv
LIST OF FIGURES vi
LIST OF TABLES x
Chapter 1 INTRODUCTION 1
Chapter 2 SOUND FIELD ANALYSIS (SFA) 5
2.1 Sparse Source Scenario 5
2.1.1 One-Stage CS Algorithm 6
2.1.2 Two-Stage MPDR and TIKR Algorithm 7
2.2 Nonsparse Source Scenario 9
2.2.1 One-Stage TIKR Algorithm 9
Chapter 3 SOUND FIELD SYNTHESIS (SFS) 10
Chapter 4 ROOM RESPONSE MEASUREMENT AND INTERPOLATION 12
4.1 Nonsparse Source Scenario 12
Chapter 5 SIMULATIONS AND EXPERIMENTS 15
5.1 Numerical Simulations 15
5.1.1 SFA Simulations 15
5.1.2 SFS Simulations 15
5.2 Experimental Investigations 17
5.2.1 One-Source Scenario 18
5.2.2 Four-Sources Scenario 21
Chapter 6 CONCLUSIONS 48
REFERENCE 49

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