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研究生: 賴奕淳
Lai, Yi-Chun
論文名稱: 利用可移動地標以機器學習為基礎機制的追蹤與定位
Tracking and Localization with Machine Learning-Based Mechanism by Moving Landmarks
指導教授: 陳文村
Chen, Wen-Tsuen
口試委員: 許健平
Sheu, Jang-Ping
王志宇
Wang, Chih-Yu
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 通訊工程研究所
Communications Engineering
論文出版年: 2017
畢業學年度: 106
語文別: 英文
論文頁數: 43
中文關鍵詞: 定位追蹤
外文關鍵詞: Localization, Tracking
相關次數: 點閱:2下載:0
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  • 移動物體的追蹤在許多應用中是不可或缺的,例如行李自動追蹤和生物追蹤。基於地標的追蹤方法通常面臨著地標部署成本與所選無線技術準確性之間的權衡。在本文中,我們提出了一種基於低功耗藍牙(BLE)的移動物體追蹤系統,該系統使用配備多個天線的移動地標。低功耗藍牙的短訊號覆蓋範圍被地標的移動性所克服。在追蹤系統中,我們通過SVM模型識別的多天線的RSSI特徵來估計AoA和目標到移動地標的距離。然後,移動地標的追蹤策略是以目標的估計相對位置為基礎。我們在EcoBT和MediaTek LinkIt ONE開發板上實現了提出的系統。實驗結果顯示,在解析度為15度時,AoA的平均誤差小於1度,在解析度為0.5公尺時,距離的平均誤差小於0.1公尺。我們進一步進行了移動目標追蹤的實驗,以顯示所提出的系統的有效性。我們還觀察到,在移動目標追蹤中存在準確度和追蹤速度之間的權衡。


    Moving object tracking is essential in many applications, such as self-tracking luggage and insect tracking. Landmark-based tracking methods usually face the tradeoff between cost in landmark deployment and accuracy of chosen wireless technology. In this thesis, we propose a Bluetooth Low Energy (BLE)-based moving object tracking system using moving landmarks equipped with multiple antennas. The short signal coverage of BLE is overcome by the mobility of landmarks. In the tracking system, we estimate the angle of arrival (AoA) and the distance from the target to the moving landmark by the pattern of RSSIs of multi-antennas recognized by the trained SVM model. The tracking strategy of the moving landmark is then based on the estimated relative location of the target. We implemented the proposed system on EcoBT and MediaTek LinkIt ONE development boards. The experiment results showed that the average error of AoA is less than 1 degree at the resolution of 15 degrees and the average error of distance is less than 0.1 m at the resolution of 0.5 m. We further conducted experiments on moving target tracking to show the effectiveness of the proposed system. We also observed that there exists a tradeoff between accuracy and tracking speed in moving target tracking.

    1 Introduction 1 2 Related Works 5 2.1 AoA-Based Localization Scheme . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Tracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Moving Landmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3 System Model and Problem Statement 8 3.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 4 AoA and Distance Estimation 13 4.1 Training of Estimation Models . . . . . . . . . . . . . . . . . . . . . . . . 14 4.2 Estimation of AoA and Distance . . . . . . . . . . . . . . . . . . . . . . . 15 5 Target Tracking 17 5.1 Stable Samples of AoA and Distance . . . . . . . . . . . . . . . . . . . . . 17 5.2 Rotation Angle and Travel Distance Control . . . . . . . . . . . . . . . . . 18 5.3 Tracking Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 6 Implementation 21 6.1 Hardware of Target . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 6.2 Hardware of Moving Landmark . . . . . . . . . . . . . . . . . . . . . . . 22 6.3 Channel Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 6.4 Synchronization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 6.5 Module Communication within the Moving Landmark . . . . . . . . . . . 26 7 Experiments 28 7.1 Measured RSSI on Different Antennas . . . . . . . . . . . . . . . . . . . . 28 7.2 Patterns of AoA at Different Distances . . . . . . . . . . . . . . . . . . . . 28 7.3 Estimated AoA and Distance . . . . . . . . . . . . . . . . . . . . . . . . . 29 7.4 Time for Collecting RSSI . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 7.5 AoA Tracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 7.6 Tracking of AoA and Distance . . . . . . . . . . . . . . . . . . . . . . . . 35 8 Conclusion and Future Works 39

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