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研究生: 陳昱任
Chen, Yu-Ren
論文名稱: 基於WiFi訊號之UVA輔助搜尋系統分析與研究
SuperDog: Assisting Searching and Rescue Operations using WiFi Signal with UAV
指導教授: 賀耀華
Ho, Yao-Hua
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2015
畢業學年度: 103
語文別: 中文
論文頁數: 43
中文關鍵詞: 無人飛行載具無線訊號搜尋路徑規劃定位演算法
英文關鍵詞: UVA, wireless signal, searching planning, localization algorithm
論文種類: 學術論文
相關次數: 點閱:138下載:6
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  • 本篇研究提出了SuperDog系統用於輔助救災,由低成本、低重量的裝置所組成,此系統有的優點包含裝置可大量複製、移動不受地表因素限制、不需安裝軟體於手持裝置上、有效縮小搜救範圍等,且輔助現有的搜尋方式,提高搜救資源的有效利用,進而提升整體搜救行動的效率,我們的研究並非要取代目前現行的搜救方法,而是使這些珍貴的資源(e.g. 搜救犬、生命探測儀),能夠更集中、更有效地利用,避免盲目地在救災區域大範圍、地毯式搜索,進而提升整體搜救過程的效率,目的是為了把握「黃金72小時」,期望能夠在有限的時間內,盡速地救出被困住的受難者。

    第一章 緒論         1 第一節 災難特性與問題描述..................................1 第二節 現行搜尋方法探討....................................3 第三節 手機裝置已備有的技術................................4 第四節 研究動機...........................................6    第二章 定位方法相關文獻探討 8 第一節 Time of Flight Based Method.......................8 第二節 Received Signal Strength Indicate Based Method....12 第三節 使用RSSI定位的修正方法..............................15 第三章 系統架構與運作流程                16 第一節 裝置構成...........................................16 第二節 網路模型假設.......................................18 第三節 系統運作流程.......................................19 第四章 定位演算法選擇                  20 第一節 DuRT方法..........................................21 第二節 Trilateration方法.................................22 第三節 定位演算法選擇實驗..................................23 第五章 搜尋路徑設計                   25 第一節 覆蓋面積導向的搜尋路徑..............................25 第二節 降低定位誤差導向的搜尋路徑..........................29 第六章 構成定位的訊號相對位置議題             32 第一節 求出符合Shadowing Model的轉換公式..................32 第二節 驗證「訊號相對位置關係影響定位」理論.................35 第七章 結論                       39 參考著作                         41

    [1]Ali-Loytty, Simo, et al. "Fingerprint kalman filter in indoor positioning applications." Control Applications,(CCA) & Intelligent Control,(ISIC), 2009 IEEE. IEEE, 2009.
    [2]Garcia-Valverde, Teresa, et al. "A Fuzzy Logic-Based System for Indoor Localization Using WiFi in Ambient Intelligent Environments." Fuzzy Systems, IEEE Transactions on 21.4 (2013): 702-718.
    [3]Hara, Shinsuke, et al. "A Perturbation Analysis on the Performance of TOA and TDOA Localization in Mixed LOS/NLOS Environments." (2013): 1-11.
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    [7]Pratap Kumar Sahu, Eric Hsiao-Kuang Wu, Member, IEEE, and Jagruti Sahoo. "DuRT: Dual Trend Based Localization for Wireless Sensor Networks." IEEE SENSORS JOURNAL, VOL. 13, NO. 8, AUGUST 2013.
    [8]Waharte, Sonia, and Niki Trigoni. "Supporting search and rescue operations with UAVs." Emerging Security Technologies (EST), 2010 International Conference on. IEEE, 2010.
    [9]Weiss, Anthony J., and Joseph S. Picard. "Maximum likelihood localization of wireless networks using biased range measurements." Communications and Information Technologies, 2007. ISCIT'07. International Symposium on. IEEE, 2007.
    [10]Will, Heiko, et al. "The membership degree min-max localization algorithm."Ubiquitous Positioning, Indoor Navigation, and Location Based Service (UPINLBS), 2012. IEEE, 2012.
    [11]Wu, Chao-Lin, et al. "An adaptive duty-cycle scheme for GPS scheduling in mobile location sensing applications." Proc. of PhoneSense (2011).
    [12]Xu, Hua, et al. "An archimedes curve-based mobile anchor node localization algorithm in wireless sensor networks." Intelligent Control and Automation (WCICA), 2010 8th World Congress on. IEEE, 2010.

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