近年來，無線感測網路的定位功能發展迅速，造就現在的發達且普及，並廣泛使用在生態環境觀察、軍事用途、採礦人員監控…等上使用，而本論文使用IEEE802.15.4/Zigbee的模組，所採用低耗電且低成本的優點，透過RSSI的定位演算法，並將座標傳送到使用者的接收端，讓使用者得知目前所有Nodes的位置。
　　本論文研究利用GPS，取得實際經緯度座標後轉換為Zigbee可接受的座標，並自動寫入Reference Node，作為Blind Node的參考座標，而讓使用者迅速得知目前所有Nodes的座標，並設計Reference Nodes的擺放位置，讓Blind Node計算出較精確的座標數值。透過本論文提出兩個方法，擴大定位範圍，所以可以使用於臨時或緊急情況需要的定位系統。

In recent years, for the prevailing of WSNs, the function of Localization tracking had widely in environmental observation. Such as: military, mining, personnel monitoring ... and so on. The equipment used in the thesis is IEEE802.15.4/Zigbee of module which is low-power and low cost. By using the RSSI localization algorithm, user can know the localization of all the Nodes.
　　In this thesis, using GPS to get the latitude and longitude coordinates and translate to the format of coordinates of Zigbee. It will automatically update the reference node, as a reference coordinate of blind node, users can know the coordinates of all existing nodes. In this thesis, we find a better position layout of the reference nodes, so blind node calculate the better accurate coordinate. We proposed two methods to expand the utilized range and can also be used for emergency system.

第一章 緒論......1
1.1 研究動機及研究目的......1
1.2 論文架構......3
第二章 相關研究......4
2.1 A Location Algorithm Integrating GPS and WSN in Pervasive Computing......4
2.2 An Intelligent Positioning Approach: RSSI-Based Indoor And Outdoor Localization Scheme In Zigbee Networks......6
2.3 A Novel Indoor RSS-Based Position Location Algorithm Using Factor Graphs......9
2.4 Distributed sensor network localization using SOCP relaxation......12
第三章 研究內容與方法......15
3.1 系統架構......15
3.2 整合GPS與Reference Node的座標......19
3.2.1 整合GPS與Reference Node的座標步驟......19
3.2.2 GPS座標數值格式......21
3.2.3 GPS度分秒與地理區域距離......21
3.2.4 GPS與定位系統座標轉換......22
3.3 定位系統流程......24
3.4 定位覆蓋範圍......27
第四章 模擬實作與結果討論......34
4.1 模擬實作說明......34
4.1.1 模擬實作目標......34
4.1.2 模擬實作環境......34
4.1.3 模擬實作界面......35
4.2 模擬結果與討論......36
4.2.1 整合GPS與Reference Node座標的模擬結果......36
4.2.2 Reference Node影響Blind Node計算座標的模擬結果......37
第五章 結論與未來相關研究......42
5.1 結論......42
5.2 未來相關研究......43
參考文獻......44
附錄—英文論文......47

圖目錄
圖2.1 GPS-WSN Node 模擬示意圖......5
圖2.2 Indoor and Outdoor localization Schemes系統架構圖(source：[Kuo 10])......6
圖2.3 三種方法在室內定位環境下 (source：[Kuo 10])......7
圖2.4 The 7th building of Yuan-Ze University-Method 1 (source：[Kuo 10])......7
圖2.5 The 7th building of Yuan-Ze University-Method 3 (source：[Kuo 10])......8
圖2.6 典型RSS室內PL System與two training point的距離 (source：[Huang 09])......9
圖2.7 PL system的Factor graph 找出(x, y, p)的座標 (source：[Huang 09])......10
圖2.8 模擬測試數據 (source：[Huang 09])......11
圖2.9 Tracking a mobile sensor node實驗(source：[Srirangarajan 08])......13
圖3.1 系統架構圖......16
圖3.2 GPS定位系統流程圖......20
圖3.3 球體示意圖......21
圖3.4 定位系統示意圖......24
圖3.5 定位系統-室外定位步驟示意圖......25
圖3.6 定位系統-室外到室內定位步驟示意圖......26
圖3.7 擴充二維平面定位範圍距離......28
圖3.8 Reference Node擴充X、Y數值......29
圖3.9 每30公尺放置一個Reference Node......29
圖3.10 產生64X64公尺定位範圍......31
圖3.11 Reference & Blind Node擴充X、Y儲存空間......32
圖3.12 擴充X、Y儲存空間後的定位過程......32
圖4.1 Reference Node的GPS Mode......35
圖4.2 定位系統-顯示Reference Node位置......36
圖4.3 定位系統-顯示Blind Node計算位置......37
圖4.4 Reference Node 擺放位置......38
圖4.5 Reference Node與Blind Node擺放位置......39
圖4.6 Blind Node座標(25,25)數據......40
圖4.7 Blind Node座標(25,15)數據......40
圖4.8 Blind Node座標(25,25)與(25,15)比較數據......41

表目錄
表3.1 擴充後範圍......27
表4.1 環境平台軟硬體設備......35
表4.2 Reference Nodes Information的GPS資料......36

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