本論文針對線性均勻的麥克風陣列訊號處理設計一自適應性空間濾波器。目的為增強期望目標訊號方向的聲音，以及降低其他方向的干擾與雜訊。本研究以線性限制最小變異(LCMV)演算法應用於增強期望目標訊號方向的聲音訊號，加上估測聲音訊號到達麥克風陣列各顆麥克風的傳遞衰減係數，藉此來調整陣列各顆麥克風放大電路的倍率，以降低各顆麥克風間的差異性，讓空間濾波器的輸出較理想，接著，再使用多通道互相關係數(MCCC)演算法估測聲音的到達方向(DOA)，以此得到空間濾波器輸入訊號之最佳延遲時間，最後研製麥克風陣列類比放大電路接收聲音訊號，實現及驗證所設計的空間濾波器系統。 This thesis investigates the signal processing of a uniform linear microphone array to design and implement an adaptive microphone-array beamforming. In practical world environments, the signal captured by a set of microphones in a speech communication system is a signal mixed with the desired signal, interference, and ambient noise. A promising solution of proper speech acquisition with reduced noise and interference in this context consists in using the linearly constrained minimum variance (LCMV) beamformining to reject the interference, reduce the overall mixture energy, and preserve the target signal. This approach requires such knowledge as the direction of arrival (DOA); therefore an estimator based on the multichannel cross correlation coefficient (MCCC) is also used. In addition, an eigenanalysis of the parameterized spatial correlation matrix is performed and reveals that such analysis allows one to estimate the channel attenuation from factors such as uncalibrated microphones. This estimate generalizes the broadband minimum variance spatial spectral estimator to more general signal models. Finally, experimental results show that the developed microphone array amplifier circuit and accompanied with signal processing algorithms successfully improve the target signal in the noisy environment.
