隨著無線通訊技術的進步以及情境感知系統的發展逐漸適用於動態環境，定位的議題逐漸被重視和大量研究。在大多數的應用系統中，相較於昂貴的感測器類型，便宜的感測器類型受研究者的喜愛、且廣泛應用的。與現有的感測系統如RFID、超音波比較起來， Zigbee 是一種便宜且低功耗的無線感測系統。近年來，低成本和易取得的特性使得接收訊號強度(Received Signal Strength, RSS)被大量應用於室內定位系統中。到目前為止，許多已提出的定位演算法宣稱在特定的環境中擁有很好的定位效能。然而，RSS對於雜訊干擾的高敏感度使得室內定位的在現實中仍是一個棘手的問題。因此，本論文致力於發展一套可靠的室內定位系統在結合量測距離取向演算法(range-based)和環境特徵比對法(range-free)的基礎上。在結合這兩種演算法的過程中，將量測距離取向演算法的理想模型以實際接收資料做修正；環境特徵比對法儲存的資料庫內容中，以RSS上下限取代平均值。為了驗證本論文所提出方法的可行性，定位系統的效能以及其他演算法的效能比較將在論文的最後呈現。

Localization has been an important issue along with the advanced wireless communications and the development of context-aware systems applicable to dynamic environment. For many applications, inexpensive sensors are preferable to the sensors with a few expensive ones. Zigbee is a cheap and low power wireless communication technique comparing to others such as RFID, ultrasound. Recently, the RSS measurements are adopted in most of the localization systems by the facts that it is low cost and provided by the communication protocol. So far, many localization schemes had been proposed and claimed to have good performances under certain environment conditions. However, the high sensitivity to noise of RSS makes the indoor localization mission in real world scenario is still a thorny problem to the researchers. In consequence, the thesis is dedicated to develop a reliable localization schemes based on the fusion of range-based algorithm and range-free algorithm. In order to verify the feasibility, the comparisons of the system and other existing approaches are provided.

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