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系統識別號 U0026-0906201011475700
論文名稱(中文) 即時室內定位系統測試平台之開發與研究
論文名稱(英文) Development of the Real Time Indoor Positioning System Test Bed
校院名稱 成功大學
系所名稱(中) 航空太空工程學系碩博士班
系所名稱(英) Department of Aeronautics & Astronautics
學年度 98
學期 2
出版年 99
研究生(中文) 蔡文明
研究生(英文) Wen-Ming Tsai
學號 p4697425
學位類別 碩士
語文別 英文
論文頁數 82頁
口試委員 指導教授-詹劭勳
口試委員-莊智清
口試委員-王大中
中文關鍵字 無線感測網路  室內定位  粒子濾波器  克利金  虛擬實境  區域性資訊服務 
英文關鍵字 Wireless Sensor Network  Indoor Positioning  Location Based Service  Particle Filter  Kriging  Geographic Information System  Virtual Reality Modeling Language 
學科別分類
中文摘要 提供使用者多元化的服務為近年來行動通訊裝置的主要發展趨勢,其中導航定位服務一直是熱門的關注焦點。目前的導航定位服務主要是仰賴全球衛星導航系統(Global Navigation Satellite System, GNSS),然而當使用者位於室內環境時,由於無法接收到衛星訊號,該定位服務勢必會被迫中止。為了提供使用者更完整的定位服務,一套完善室內定位系統是必要的。故本論文使用無線感測網路之接收訊號強度(Received Signal Strength)環境特徵演算法進行室內定位,其中考量儀器功耗,本論文採用ZigBee無線傳輸模組來建構定位系統。環境特徵演算法主要是將使用者收集的資訊與預先建立好的環境資訊資料庫進行比對進而找出使用者最有可能出現的位置,其中本論文討論的演算法有最近鄰居演算法(Nearest Neighbor)、加權最近鄰居演算法(K-Weighted Nearest Neighbors)及機率判定法(Probabilistic Approach)。本論文將針對以上三種比對演算法作定位效能上的評估並且結合粒子濾波器演算法(Particle Filter)來改善動態定位結果。然而使用環境特徵演算法必須投入人力及時間在於定位資料庫的蒐集及建置,如果室內空間範圍較大,那麼便會增加定位系統建置時間及人力成本。為了有效減少定位資料庫的建置成本。本論文採用克利金(Kriging)演算法來輔助定位資料庫的建立。
另外,為了提供完整的區域性資訊服務(Location Based Service, LBS)。本論文亦提出一套三維區域性圖資系統的開發流程,透過整合虛擬實境技術與電腦輔助設計繪圖軟體讓開發人員可以快速開發出一套符合目標需求的圖資系統並且減化未來系統的更新成本。最後本論文成功開發出一套以國立成功大學航太系館為例的即時室內定位系統(Real Time Indoor Positioning System, RTIPS)測試平台。
英文摘要 The Location Based Service (LBS) is becoming a popular application for mobile users, and users can use mobile devices to get their current positions and search for other information based on their locations. These applications use Global Navigation Satellite System (GNSS). However, due to the GNSS signal propagation limit, the positioning and navigation services are terminated when the users are in the indoor environments. To provide complete positioning and navigation services, an indoor LBS system is proposed in this thesis. The Wireless Sensor Network (WSN) is used to realize the indoor positioning system. Considering the power consumption, the ZigBee radio is used in this work, and the positioning algorithm is the fingerprinting method based on the Received Signal Strength (RSS). The main concept of the fingerprinting method is to conduct the pattern recognition for the estimation of the user location. In this thesis the positioning performances are investigated for different matching algorithms including the Nearest Neighbor (NN) algorithm, the K-Weighted Nearest Neighbors (KWNN) algorithm with different values of K, and the probabilistic approach based on the kernel method. Additionally, to enhance the accuracy and yield the smoother positioning results, the particle filter is used to improve the performance of the indoor positioning system. Since the fingerprinting method needs to build the positioning database, the creation of the positioning database for a large indoor area is a time consuming work. To reduce the workload and time, the Kriging algorithm is applied to extend the positioning database efficiently based on some RSS measurements.
Finally, a rapid and practical procedure is proposed for the development of a 3D Geographic Information System (GIS) by integrating the Computer-Aided Design (CAD) software and the Virtual Reality Modeling Language (VRML) technique. The Department of Aeronautics and Astronautics at National Cheng Kung University is used as an example to successfully demonstrate the Real Time Indoor Positioning System (RTIPS) test bed.
論文目次 摘要 ............................................... I
ABSTRACT ........................................... III
ACKNOWLEDGEMENTS ................................... V
LIST OF CONTENT .................................... VI
LIST OF TABLES ..................................... VIII
LIST OF FIGURES .................................... IX
Chapter 1 INTRODUCTION ............................. 1
1.1. Motivation .................................... 1
1.2. Review of Literatures ......................... 2
1.3. Objectives .................................... 4
1.4. Thesis Organization ........................... 5
Chapter 2 INDOOR POSITIONING ALGORITHMS ............ 7
2.1. The Nearest Neighbor Algorithm ................ 10
2.2. The K-Weighted Nearest Neighbors Algorithm .... 10
2.3. The Probabilistic Approach .................... 12
2.4. The Particle Filter ........................... 14
2.5. The Kriging Algorithm ......................... 20
2.6. Summary ....................................... 24
Chapter 3 GEOGRAPHIC INFORMATION SYSTEM ............ 25
3.1. The Virtual Reality Modeling Language ......... 26
3.2. The Development of the 3D Geographic
Information System .............................27
3.3. Summary ....................................... 31
Chapter 4 EXPERIMENT RESULTS ....................... 32
4.1. ZigBee Protocol ............................... 32
4.2. Experiment Setup .............................. 33
4.3. Experiment Results ............................ 41
4.4. Summary ....................................... 63
Chapter 5 THE REAL TIME INDOOR POSITIONING SYSTEM... 64
5.1. The Data Training ............................. 64
5.2. The Positioning ............................... 67
5.3. The Search Service ............................ 71
5.4. Summary ....................................... 75
Chapter 6 CONCLUSIONS AND FUTURE WORKS ............. 77
6.1. Conclusions ................................... 77
6.2. Future Work ................................... 78
REFERENCES ......................................... 79
BIOGRAPHY .......................................... 82
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