近年來，已開發出許多無線感測網路定位的應用，例如應用於室內人員和物件的移動追蹤、監控…等。其中IEEE 802.15.4/ZigBee無線通訊網路系統低耗電、低成本的特性，使得ZigBee成為目前廣泛使用的無線感測網路定位系統之一。然而一般ZigBee無線感測定位系統定位時，需事先佈建好定位參考點，若在沒有事先佈點且沒有適當量測工具的狀況下臨時要執行定位應用，以人工量測設定全部參考點的座標資料較為耗時耗力且不便，較無法達到臨時性應用的需求。
本論文研究建置一個動態定位系統，除了初始參考點以外其他參考點可自動計算並設定好自身定位座標資料，且在定位過程中若參考點遭到位移，透過定時自動校正的功能，在一定的時間內參考點將會自動校正定位座標資料，最後透過Dead-Reckoning Algorithm修正偵測到物體移動路線的誤差。

In recent years, a number of wireless sensor network localization applications have been developed, such as personnel and object monitoring, and so on. Of all, IEEE 802.15.4/ZigBee wireless sensor network localization system has the features of low-power and low-cost, so it has become one of the widely used wireless sensor network localization systems. However, the chief drawback is that its Reference Node needs setting up in advance and if there are no appropriate measurement tools, it would be quite inconvenient and time-consuming to set it up manually.
In this thesis, we propose a dynamic indoor localization system in which Reference Node can automatically calculates and sets up its own coordinates and we make Reference Node regulate its coordinates within a particular period of time. And finally we use the Dead-Reckoning Algorithm to correct the path of detected objects.

第一章 緒論 1
1.1 研究動機與目的 1
1.2 論文架構 3
第二章 相關研究 4
2.1 An Environment Adaptive ZigBee-based Indoor Positioning Algorithm 4
2.2 An Effective Pedestrian Dead-Reckoning Algorithm Using a Unified Heading Error Model 5
2.3 Location Tracking Based on Wireless Sensor Network	7
第三章 研究內容與方法 8
3.1 系統架構 9
3.1.1 Coordinator	9
3.1.2 Reference Node 10
3.1.3 Blind Node 11
3.2 動態安裝參考點步驟 14
3.3 Blind / Reference State 切換機制	15
3.4 轉換與動態佈建參考點示意圖 17
3.5 定時自動校正Reference Node座標 20
3.6 修正所偵測到物體移動的誤差 21
3.6.1 誤差修正的特殊狀況討論 26
第四章 模擬實作與結果討論 29
4.1 模擬實作說明 29
4.1.1 模擬實作目標 29
4.1.2 實作環境 30
4.1.3 動態安裝參考點實作 30
4.1.4 物體移動偵測錯誤位置與誤差修正結果 36
4.2 模擬結果與討論 44
第五章 結論與未來相關研究 45
5.1 結論 45
5.2 未來相關研究 46
參考文獻 47
附錄—英文論文 49


圖目錄
圖2.1 Localization Phase(source:[Larranaga 10]) 5
圖2.2 The hardware of the MSP(source:[Chen 10]) 6
圖2.3 The PDR algorithm architecture of the MSP(source:[Chen 10]) 6
圖2.4 RSS based pattern matching algorithm(source:[Wang 10]) 7
圖3.1 系統架構圖 9
圖3.2 RSSI轉換距離 11
圖3.3 Blind Node定位示意圖 12
圖3.4 Blind Node狀態轉換目的示意圖 13
圖3.5 動態安裝參考點流程圖 14
圖3.6 切換為Reference State後執行的工作 16
圖3.7 切換為Blind State後執行的工作 16
圖3.8 轉換與動態佈建參考點示意圖 19
圖3.9 定位系統Reference Node位移 20
圖3.10 Blind Node State Switch 21
圖3.11 物體移動偵測的誤差 21
圖3.12 移動偵測雜訊過濾條件 22
圖3.13 移動偵測誤差修正方法一 23
圖3.14 修正方法一修正示意圖 24
圖3.15 移動偵測誤差修正方法二 25
圖3.16 修正方法二修正示意圖 26
圖3.17 Case 1修正誤差狀況 27
圖3.18 Case 2修正誤差狀況 28
圖4.1 無佈點定位環境(淡江大學工學大樓E689) 30
圖4.2 設置初始參考點 31
圖4.3 初始參考點實際擺放位置 31
圖4.4 Blind Node定位 32
圖4.5 Blind Node實際位置 32
圖4.6 移動Blind Node 33
圖4.7 Blind Node實際移動情形 33
圖4.8 Blind Node切換為Reference State 34
圖4.9 其它Blind Node定位 34
圖4.10 其它Blind Node狀態切換 35
圖4.11 新建參考點的功能測試 35
圖4.12 參考點測試實際擺放圖 36
圖4.13 L型路徑原始偵測數據 37
圖4.14 L型路徑方法一修正結果 37
圖4.15 L型路徑方法二修正結果 37
圖4.16 鏡射現象原始偵測數據 38
圖4.17 鏡射現象方法一修正結果 38
圖4.18 鏡射現象方法二修正結果 39
圖4.19 方形路徑原始偵測數據 39
圖4.20 方形路徑方法一修正結果 40
圖4.21 方形路徑方法二修正結果 40
圖4.22 倒L型路徑原始偵測數據 41
圖4.23 倒L型路徑方法一修正結果 41
圖4.24 倒L型路徑方法二修正結果 41
圖4.25 方形原始偵測 43
圖4.26 方形修正方法一 43
圖4.27 方形修正方法二 43


表目錄
表4.1 環境平台軟硬體設備 30

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