隨著處理器技術與無線通訊技術的發展，無線感測網路科技可望對我們日常生活有顯著的影響；其應用也已提供許多領域前所未有的契機。在大部分的應用中，首要的議題便是如何定位感測網路中的節點位置。近年來發展適用於室內環境的無線感測網路定位系統，可以採用廉價且普遍應用的接收訊號強度(Received Signal Strength, RSS)之量測而達到定位的服務。
雖然定位演算法已發展許久且普遍宣稱可於特定條件下達到理想定位精確度，但是基於RSS的室內定位系統的發展於現實環境中仍然處於困境。其主要原因是由於RSS本身特性極易受到雜訊、環境以及量測誤差的影響而導致訊號品質變差進而影響定位結果。有鑑於此，本論文發展及實現離群值偵測技術應用於定位演算中，並提出新的離群值偵測技術可偵測並加以處理資料列中的雜訊以及錯誤資料進而降低定位誤差。此外，本論文更建置了一套室內定位系統並設計了輕巧可攜的手錶型式使用者裝置；如此一來，本論文所提出的定位演算流程與離群值偵測技術即可實現於實際環境中。根據模擬與實驗結果顯示，本論文所提出的離群值偵測技術定位流程的確可偵測出資料列中離群值並降低定位誤差。

Along with the advances of the processor technologies and wireless communications, the wireless sensor network (WSN) technology is expected to have salient influences on our daily life and its proposed applications already provide unprecedented opportunities in various domains. In most of these applications, the primary issue is to locate the location of nodes in the sensor network. To locate the nodes, the cheap and widely available measurement technique – received signal strength (RSS) – is usually taken into the indoor localization system.
Although a myriad of sophisticated localization algorithms have been developed and claim to have acceptable results under certain circumstances, the RSS-based indoor localization systems in real world scenario are still mired in difficulties due to the RSS intrinsic sensitivity to noise, environment as well as measurement error. As a result, this thesis is dedicated to develop and implement localization procedure with outlier detection technique and propose a new outlier detection scheme which can detect the noisy data and error in data sequence and proceed to cope with it. Furthermore, this thesis constructs an RSS-based indoor localization system based on ZigBee protocol and designs a portable watch-type user device so that the proposed outlier detection scheme can be adopted into the real world scenario and each device can determine its position by itself. According to the experimental results, the proposed outlier detection scheme can indeed detect the outliers in the target data sequence and also mitigate the localization and tracking error.

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