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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 黃寶儀(Polly Huang) | |
dc.contributor.author | Seng-Yong Lau | en |
dc.contributor.author | 劉承榮 | zh_TW |
dc.date.accessioned | 2021-06-07T17:51:59Z | - |
dc.date.copyright | 2012-09-03 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-08-20 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15780 | - |
dc.description.abstract | 隨著室內定位系統的產值將於2016年達到27.1億美元。能夠支援在日常生活環境中持續使用的室內定位系異發重要。大多數的定位系統都使用接收訊號強度來進行定位。環境中預先安裝的Beacon會不斷的發射封包,接收節點會收集封包的訊號強度,傳送到定位主機來進行比對以找出位置。
在這篇論文中,我們根据實際的需求,實際設計了供定位系統使用的接收器。這個接收器經過了三個版本的改良及演進,成為符合實際使用需要的硬體。同時,我們也在校園內的系館、醫院及台北世貿展覽館中實際佈建了室內定位系統的測試平台。這些平台除了能提供定位的服務,也同時能進行各項的測試實驗。利用這些測試平台,我們進行了一系列的量測實驗,以便了解各項影響室內定位系統效能的因素。我們發現影響定位系統效能的主要因素為:Wifi網路的干擾、人體的屏障造成接收訊號強度改變、以及使用者的速度變化。 針對Wifi網路的干擾的問題,我們提出了一個跳頻機制。實驗的結果證明,在Wifi的影響最大的時候,這個跳頻機制能讓定位系統的誤差從2.74公尺降到1.24公尺。我們也提出了一個由陀螺儀來輔助的定位方法。這個方法可以避開人體屏障所造成的影響,讓80百分段的定位準確度提高46%。最後,我們利用加速度計偵測使用者的速度變化,來即時調整粒子濾波器的設定,使我們的定位系統能夠跟上使用者速度的變化,即使在跑動中也能準確的定位。 | zh_TW |
dc.description.abstract | With an expected market value of $2.71 billion in 2016, supporting daily use of real-time location systems in households and commercial buildings is an increasingly important subject of study. Most indoor localization systems employ an RSSI-signature-based approach which exploits temporal stability in the received signal strength indication (RSSI) from a set of pre-deployed beacons at identified locations, which is referred to as the RSSI signature.
In this dissertation, three generations of the location tracking node are designed to address the need of real-time indoor location system. Tightly cooperate with the potential users from elderly care facility, several application specific requirements are considered in the hardware design. Three wireless sensor network deployments in different daily environments including office building, hospital, and exhibition hall are demonstrated. These deployments provide location service to the users and serve as an experimental testbeds. Several measurement studies are conducted on the testbeds to gain a better understanding of the performance of indoor location system. With in-depth analysis of the measurement results, major factors that influence the performance are identified. These factors are WiFi interference, mobility pattern variation, and human body obstacle. A frequency hopping mechanism is proposed to cope with WiFi interference problem. Experimental results show that the 80th-percentile localization error can be reduce from 2.74 meters to 1.24 meters (55%) when 802.11 traffic rate is at its peak. Another gyro assisted orientation aware method is proposed to solve the human bod obstacle problem. With this mechanism, the 80-percentile localization accuracy can be improved by 46%. Finally, an accelerometer assisted adaptive particle filter is proposed to target the mobility pattern variation problem. The experiment result shows the location system can adapts to the walking speed variation even in the extreme case like running. | en |
dc.description.provenance | Made available in DSpace on 2021-06-07T17:51:59Z (GMT). No. of bitstreams: 1 ntu-101-F92921102-1.pdf: 4677470 bytes, checksum: 7e8fa4be9bd4366c5faa59ccb80dd7ae (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | List of Figures vii
List of Tables xi 1 Introduction 1 1.1 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.2 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2 Related Work 11 2.1 Indoor Location Systems . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Hardware and Deployment . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3 Measurement Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.4 Sensor Assisted Solution . . . . . . . . . . . . . . . . . . . . . . . . . 16 3 System, Hardware and Deployment 19 3.1 Location System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.1.1 Beacon And Receiving Tag . . . . . . . . . . . . . . . . . . . . 21 3.1.2 Training Phase . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.1.3 Tracking Phase and the KNN Estimator . . . . . . . . . . . . 23 3.1.4 Particle Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.1.5 Data Dissemination . . . . . . . . . . . . . . . . . . . . . . . . 26 3.2 Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.2.1 Beacon and Relay Nodes . . . . . . . . . . . . . . . . . . . . . 27 3.2.2 First Generation Receiving Tag . . . . . . . . . . . . . . . . . 29 3.2.3 Second Generation Receiving Tag . . . . . . . . . . . . . . . . 31 3.2.4 Third Generation Receiving Tag . . . . . . . . . . . . . . . . . 33 3.2.5 Hardware Evaluation . . . . . . . . . . . . . . . . . . . . . . . 38 3.3 Deployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.3.1 General Architecture . . . . . . . . . . . . . . . . . . . . . . . 42 3.3.2 USB Connectivity . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.3.3 Power Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3.3.4 BL Building Testbed . . . . . . . . . . . . . . . . . . . . . . . 46 3.3.5 Bei-hu Hospital Testbed . . . . . . . . . . . . . . . . . . . . . 47 3.3.6 World Trade Center . . . . . . . . . . . . . . . . . . . . . . . 49 3.3.7 Lessons Learned . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4 Wifi Interference And Channel Hopping 55 4.1 WiFi Interference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.1.1 Data Logging . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.1.2 Loss in Beacon Message Logging . . . . . . . . . . . . . . . . . 58 4.1.3 Beacon Message Synchronization . . . . . . . . . . . . . . . . 60 4.1.4 Result of Localization Errors . . . . . . . . . . . . . . . . . . . 60 4.1.5 Impact of General Beacon Message Losses . . . . . . . . . . . 62 4.1.6 Impact of Individual Beacon Message Loss . . . . . . . . . . . 64 4.1.7 Impact of RSSI Value Instability . . . . . . . . . . . . . . . . 66 4.1.8 Implication . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.2 Channel Hopping Mechanism . . . . . . . . . . . . . . . . . . . . . . 71 4.2.1 Beacon Node . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.2.2 Diagnostic Test . . . . . . . . . . . . . . . . . . . . . . . . . . 72 4.2.3 Signalling Protocol . . . . . . . . . . . . . . . . . . . . . . . . 78 4.3 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.3.1 Trace Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . 79 4.3.2 Hopping Time . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.3.3 PRR Thresholds Diagnostic Test . . . . . . . . . . . . . . . . 82 4.3.4 Hidden Markov Model . . . . . . . . . . . . . . . . . . . . . . 84 4.3.5 Localization Error With Channel Hopping . . . . . . . . . . . 88 5 Orientation Aware Localization 93 5.1 Microscopic Examination . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.1.1 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . 94 5.1.2 Data Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 5.1.3 Impact Of Antenna Orientation . . . . . . . . . . . . . . . . . 95 5.1.4 Impact Of Foreground Obstacle . . . . . . . . . . . . . . . . . 97 5.1.5 Impact Of Background Obstacle . . . . . . . . . . . . . . . . . 97 5.1.6 Impact Of Beacon Density . . . . . . . . . . . . . . . . . . . . 99 5.1.7 Implication . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 5.2 Gyro Assisted Orientation Aware Localization . . . . . . . . . . . . . 103 5.2.1 Heading Information Detection . . . . . . . . . . . . . . . . . 103 5.2.2 System Architecture . . . . . . . . . . . . . . . . . . . . . . . 105 5.2.3 Data Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . 106 5.2.4 Signal Processing . . . . . . . . . . . . . . . . . . . . . . . . . 107 5.2.5 Min-Max Method . . . . . . . . . . . . . . . . . . . . . . . . . 111 5.3 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 5.3.1 Experiment Setting . . . . . . . . . . . . . . . . . . . . . . . . 113 5.3.2 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 6 Mobility Aware Particle Filter 117 6.1 Moving Pattern Variation . . . . . . . . . . . . . . . . . . . . . . . . 117 6.1.1 Experiment Setup . . . . . . . . . . . . . . . . . . . . . . . . . 118 6.1.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 6.1.3 Implication . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 6.2 Accelerometer Assisted Mobility Aware Particle Filter . . . . . . . . . 124 6.2.1 Accelerometer Based Step Counting . . . . . . . . . . . . . . . 124 6.2.2 Fast Fourier Transform . . . . . . . . . . . . . . . . . . . . . . 127 6.2.3 Mobility Aware Particle Filtering . . . . . . . . . . . . . . . . 131 6.3 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 6.3.1 Stride Frequency Estimation . . . . . . . . . . . . . . . . . . . 132 6.3.2 Location Estimate . . . . . . . . . . . . . . . . . . . . . . . . 133 6.3.3 Synthesized Test Speed Variation . . . . . . . . . . . . . . . . 136 6.3.4 Stride Length Setting . . . . . . . . . . . . . . . . . . . . . . . 137 7 Conclusion 141 References 143 | |
dc.language.iso | en | |
dc.title | 無線感測網路室內定位系統之硬體設計、佈建、量測與改善 | zh_TW |
dc.title | Wireless Sensor Network Indoor Localization System: Hardware Design, Deployments, Measurements, and Improvements | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 許建平,朱浩華,陳恆順,陳伶志,藍崑展 | |
dc.subject.keyword | 無線感測網路,室內定位系統, | zh_TW |
dc.subject.keyword | Indoor Localization,Interference,Sensor-assisted,Testbed, | en |
dc.relation.page | 152 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2012-08-21 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
顯示於系所單位: | 電機工程學系 |
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ntu-101-1.pdf 目前未授權公開取用 | 4.57 MB | Adobe PDF |
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