隨著低功號藍牙 (BLE) Beacon 成為一個重要的近距離傳輸技術，基於低功號藍牙Beacon 的無線電頻率 (Radio Frequency) 指紋成為一個熱門的室內定位方法。在Beacon 室內定位系統中設備多樣性 (Device Diversity) 是一個很基礎的問題，會造成使用者裝置收到的RSSI 值與參考裝置不同，進而導致定位的不精確。這個議題隨著現代裝置種類的快速成長而愈來愈受到重視。在這篇論文中我們實作了四種已知的方法 (Linear Calibration, SSD, DIFF, Cosine Similarity) 來解決設備多樣性的問題。實驗結果顯示這些已知的方法在我們的環境中效果並不好，因此我們結合了更多資訊，設計並實作一個室內定位系統。為了驗證我們的系統，我們在國立成功大學圖書館建立一個實驗環境、收集真實世界的數據來做實驗。實驗結果顯示我們的系統誤差距離小於一公尺相較於已知的方法改善了約25%。此外，我們也減少預測位置與實際位置中出現障礙物的機會，稱之為能見機會 (Visibility Probability)。在像是導航及目標尋找等應用中，是否能看見目標相當重要，我們探討它所帶來的影響並試著改善，實驗結果顯示我們的系統將能見機會從78.57%提升至91.38%。

As Bluetooth Low Energy (BLE) beacon becomes one of the most important new mobile technologies to deliver proximity services to users, Radio Frequency (RF) fingerprinting based on BLE beacon is popular for indoor localization. In beacon-based indoor positioning system, device diversity is a fundamental problem which leads to
uncertain positioning results due to RSSI value difference between user device and reference device. This problem becomes more important in recent years because of
the tremendous growth of mobile devices. In this thesis, we implement four existing methods against device diversity including linear calibration, signal strength difference (SSD), difference of signal strength (DIFF), cosine similarity and compare their performance. Because of the unsatisfactory improvement, we design and implement an indoor positioning system taking more information into consideration. To validate our system, we build a testbed at NCKU library, collect real-world data for our experiments. The average positioning error of our system is less than one meter and reduces 25% compared with the existing methods. Moreover, we also reduce the chance of existing obstacles between real position and predicting position which is called visibility probability. Visibility is important for some applications, such as navigation and target finding, we discuss the influence and try to improve it. Our experimental results show that our system improves the visibility probability from 78.57% to 91.38%.

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