音源定位可應用於很多領域，包含玩具、電視會議以及安全的應用等，為了將來能有效地實作在微處理器上，所發展的演算法則必須是成本較低、運算簡單的方法，所以我們在時域上研究可行的演算法，建立「音源定位系統」，來估算二維空間中的音源入射方向角。
「音源定位系統」主要是利用音源的傳遞到達兩個麥克風的時間差TDOA （Time Difference of Arrival），來估算音源可能的入射方向角，而本論文著重在如何估算TDOA，並實作了論文中所提的時域上的四種方法，包含「AMDF（Average Magnitude Difference Function）」、「ratioAMDF」、「最小平方法」以及「Cross Correlation」。
實驗上包含三大部份：（1）針對單句非移動中（non-moving）音源的語料所估算的TDOA，可看出環境對TDOA的影響及TDOA的變化趨勢。（2）針對所有非移動中音源的語料，分別以四種時域方法估算TDOA的辨識結果，而辨識結果幾乎都有八成左右的辨識率，（3）針對移動中音源的語料所估算的TDOA，可看出估算出來的音源方向角隨著音源的移動而產生的變化趨勢，的確與預估的結果一樣。

The goal of source localization is to estimate the direction angle of source by means of Time Difference of Arrival (TDOA). In this research, we focus on how to estimate TDOA and implement four mentioned time domain methodologies, AMDF, ratioAMDF, Least Squares, and Cross Correlation.
Our experiment results demonstrate that almost all of the accuracy rates estimated by the four TDOA methodologies are about eighty percent. Furthermore, the costs of these methodologies are low. Therefore, these methodologies are not only able to be carried out on microcontrollers but also credible.

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