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系統識別號 U0026-0812200915170053
論文名稱(中文) 無線感測網路之定位演算法
論文名稱(英文) Localization Algorithm in Wireless Sensor Network
校院名稱 成功大學
系所名稱(中) 電信管理研究所
系所名稱(英) Institute of Telecommunications and Management
學年度 97
學期 2
出版年 98
研究生(中文) 黃琦雯
研究生(英文) Chi-wen Huang
學號 R9695402
學位類別 碩士
語文別 英文
論文頁數 54頁
口試委員 口試委員-林珮珺
口試委員-林易泉
指導教授-陳文字
口試委員-林福林
中文關鍵字 接受訊號強度  定位演算  無線感測網路 
英文關鍵字 positioning algorithm  Received Signal Strength (RSS)  Wireless sensor network (WSNs) 
學科別分類
中文摘要 隨著科技發展,無線感測網路已成為本世紀最熱門的研究之一,目前廣泛應用於環境生態監控、遠距醫療照護與個人定位等民生用途,近年來發展適用於室內環境的無線感測網路定位系統,可採用接收訊號強度RSS(Received Signal Strength)之訊號特性來進行定位。本論文利用IEEE 802.15.4 /ZigBee模組來建置低成本與低耗電特性之無線感測網路,藉由量測模組訊號強度,自行撰寫定位演算法,並規劃室外環境之定位區域、定位用固定節點座標及其相關參數設定,透過分析移動與固定位置間之訊號強度衰減情形,發展定位演算法估算移動點位置資訊。經由量測訊號與定位實驗,本研究所提出之定位演算法可達到1公尺以內的定位誤差。本研究未來可提供作為定位系統參數校正之參考,並實際應用於室內外隨機佈點的無線感測網路系統,如遠距照護病人追蹤及物流管理等,未來將可結合各種類之感測器以提供多樣化的定位資訊與數位服務。
英文摘要 Recent technological advances have made the wireless sensor network a very important research issue. There are also plenty of novel applications emerging, such as habitat and medical care, smart environmental monitoring, indoor energy management, and target tracking. In this research, we have implemented a low cost and low power consumption localization system that uses Received Signal Strength (RSS) in a sensor network based on the IEEE 802.15.4/ZigBee standard. We integrate empirical measurements with signal propagation modeling to determine user locations. We present several experimental results in different environments that demonstrate the ability of our localization algorithm to estimate user location with high accuracy. The estimation error of our localization algorithm is less than one meter.
論文目次 Content
Chapter 1 Introduction 1
1.1 Background 1
1.2 Motivation and Objective 5
Chapter 2 Literature Review 7
2.1 IEEE 802.15.4/ZigBee 7
2.1.1 Wireless Sensor Network 7
2.1.2 ZigBee Alliance 9
2.1.3 IEEE 802.15.4/ZigBee Standard 10
2.2 Positioning Method 15
2.2.1 Related Ranging Method 15
2.2.2 Received Signal Strength 18
2.2.3 Signal Strength Based Positioning Algorithm 20
2.2.4 Triangulation 23
Chapter 3 Proposed Algorithm 25
3.1 Proposed Algorithm 25
3.1.1 System Process 25
3.1.2 Positioning Technique 27
3.2 Experiment Design 31
3.2.1 Module Introduction 31
3.2.2 Measurement Environments 34
3.2.3 Relation between RSS and Distance 36
3.2.4 Measuring RSS of blind node 41
Chapter 4 Results 45
4.1 Localization Results 45
4.2 Measurement Error 47
Chapter 5 Conclusion and Future Work 50
Reference 51
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