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題名 利用智慧型行動裝置與場景約制進行室內導航定位之研究
Using Smart Mobile Device for Indoor Navigation with Scene Constraint作者 吳東旂
Wu, Dong Chi貢獻者 甯方璽
Ning, Fang Shii
吳東旂
Wu, Dong Chi關鍵詞 室內定位
行人航位推算
Savitzky-Golay Filter
場景約制
Indoor position
Pedestrian Dead Reckoning
Savitzky-Golay Filter
Scene Constraint日期 2016 上傳時間 2-九月-2016 00:51:39 (UTC+8) 摘要 隨著智慧型行動裝置及導航定位科技的快速發展，導航定位已成為目前日常生活上不可或缺的工具，室外的導航定位可以利用全球導航衛星系統(Global Navigation Satellite System, GNSS)導航訊號進行，但是室內定位部分由於訊號遮蔽，導致無法接收GNSS訊號進行導航定位，因此室內定位的各類方式應運而生，如Wireless、藍芽、無線射頻技術(Radio Frequency IDentification，RFID)、iBeacon等。每種不同的室內定位方式有不同的使用成本，使用成本直接影響室內定位方法的使用門檻。因此本研究透過使用行動裝置之微機電系統(Micro Electro Mechanical Systems，MEMS)獲取陀螺儀與加速度儀資訊，並且經由濾波器平滑訊號後偵測行走步伐，再透過最小二乘擬合方式進行步距估計，以行人航位推算(Pedestrian Dead Reckoning，PDR)方式求得位置坐標，另外亦透過場景建置地圖，依計算所得坐標與參考點之方位角與轉彎特徵尋找來判斷坐標校正時機，並將坐標校正為該時間坐標之相對正確位置。本研究結果顯示使用Savitzky-Golay Filter有助於提升步伐偵測準確性，且透過方位角計算的判斷依據與轉彎特徵判斷可以有效提升定位精度，於先期驗證中閉合差約為2.352公尺，後期驗證閉合差可達0.99公尺。
The widespread adoption of mobile device has improved the accuracy of navigation and location. Since nowadays Global Navigation Satellite System (GNSS) is easier to be installed in the mobile device to locate and navigate in the outdoors. Signals of GNSS are obstructed so navigation and positioning would be hard task to be executed indoors. Hence, methods of indoor positioning appear as the instruments of Bluetooth, RFID, IBeacon etc. Every method of indoor positioning has its respective cost to affect the selection of indoor positioning technique. In this study, uses data of gyroscope and accelerometer from Micro Electro Mechanical Systems (MEMS) and detects footsteps by using filter to smooth the signal, and then estimate the step length by the ordinary least square. Finally, use Pedestrian Dead Reckoning (PDR) to compute coordinates and use azimuth and the feature of turning to decide time of adjusting position. The results of this study show using the Savitzky-Golay Filter detecting footsteps and applying azimuths and turning feature adjusting coordinate can get the closure of the early test trial for 2.352m and in the post-test scene, the closure can be improved to 0.99m.參考文獻 中文參考文獻王冬暉、許占文，「一種基於類投影的地圖匹配算法」，『瀋陽工業大學學報』，25(5):433-436。 王敏、魏衡華、鮑遠律，2012，「GPS導航系統中的地圖匹配算法」，『計算機工程』，38(14):259-261。 王楠、王勇峰，1999，「一種基於位置點匹配的地圖匹配算法」，『東北大學學報:自然科學板』，20(4):344-347。 江凱偉，2005，「空間定位技術發展之現況及未來展望」，『國土資訊系統通訊』，56。曲衍旭、郭倫嘉、張聖安、薛毓弘、馮堃齊、黃義雄，2012，「一結合無線訊號強度與慣性元件進行跨裝置間定位的系統與方法」，『電腦與通訊』，143:43-48。 李金鳳、王慶輝、劉曉梅，曹順、張慕遠,2014,「基於MEMS慣性傳感器的行人航位推算系統」，『傳感器與微系統』，33(12):85-87。 李清泉、黃練，「基於GPS軌跡數據的地圖匹配算法」，『測繪學報』，39(2):207-212。 林惠玲、陳正倉，2002，『應用統計學』四版修訂版，台北:雙葉書廊有限公司。 祁忠勇，1994，『FFT與訊號處理簡介』，演講紀錄。 姜仁傑、高永威、馮堃齊、陳威寧、林念真、林宛蓉，2014，「具多姿態步距校正之室內定位系統」，『電腦與通訊』，157:21-28。 柳林，2007，「移動終端導航系統中地圖匹配技術的研究與應用」，山東科技大學地圖製圖學與地理信息工程專業博士論文:山東 胡安東、王堅、高井祥，2014，「一種基於地圖匹配輔助行人航位推算的室內定位方法」，『測繪科學技術學報』，31(5):529—532。 陳會安，2015，「新觀念 Android程式設計範例教本 使用Android Studio」，台北，旗標出版股份有限公司。 彭威然，2014，「使用手機加速度計和陀螺儀之室內定位」，淡江大學資訊工程學系網路與通訊碩士班學位論文:新北。 楊凡、趙東東，2012，「基於 Android平台的WiFi定位」，『電子側量技術』，35(9):116-119。 楊東凱、寇艷紅、吳金培、張其善，2003，「智能交通系统中的地图匹配定位方法」，『交通運輸系統工程與信息』，3(3):38-43。 英文參考文獻Attia, M., Moussa, A., & El-Sheimy, N., 2013, “Map aided pedestrian dead reckoning using buildings information for indoor navigation applications”, Positioning. Beauregard, S.,Haas, H. ,2006, ”Pedestrian dead reckoning: A basis for personal positioning”. Paper presented at the Proceedings of the 3rd Workshop on Positioning, Navigation and Communication. Beauregard, S., Klepal, M.,2008, “Indoor PDR performance enhancement using minimal map information and particle filters”, Position, Location and Navigation Symposium ,2008 IEEE/ION. IEEE, 2008. 141-147. Bullock, J. ,Krakiwsky, E. ,1994,” Analysis of the use of digital road maps in vehicle navigation”. Position Location and Navigation Symposium, IEEE. Chen, G., Meng, X., Wang, Y., Zhang, Y., Tian, P., & Yang, H.,2015,” Integrated WiFi/PDR/Smartphone Using an Unscented Kalman Filter Algorithm for 3D Indoor Localization”,Sensors,15(9):24595-24614. Gilliéron, P. Y., Büchel, D., Spassov, I., & Merminod, B., 2004, “ Indoor navigation performance analysis”, ENC GNSS, 30. Goyal, P., Ribeiro, V. J., Saran, H., & Kumar, A., 2011, “Strap-down pedestrian dead-reckoning system”, measurements , 2:3. Groves, P. D., 2013, 『Principles of GNSS, inertial, and multisensor integrated navigation systems』, Artech house.Grove, P.D., “Principles of Integrated Navigation,” Course Notes, QinetiQ Ltd., 2002. Koifman, M., & Bar-Itzhack, I., 1999, “Inertial navigation system aided by aircraft dynamics”, Control Systems Technology, IEEE Transactions on, 7(4):487-493. Kroger, T., Chen, Y., Pei, L., Tenhunen, T., Kuusniemi, H., Chen, R., & Chen, W., 2010, “Method of pedestrian dead reckoning using speed recognition.”, Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), 1-8.Liu, Y., Chen, Y., Shi, L., Tian, Z., Zhou, M., & Li, L., 2015, “Accelerometer Based Joint Step Detection and Adaptive Step Length Estimation Algorithm Using Handheld Devices”, Journal of Communications, 10(7). Marschollek, M., Goevercin, M., Wolf, K.-H., Song, B., Gietzelt, M., Haux, R., & Steinhagen-Thiessen, E. ,2008,.” A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons”. Paper presented at the Engineering in Medicine and Biology Society. ,30th Annual International Conference of the IEEE. Niu, X., Zhang, Q., Li, Y., Cheng, Y., & Shi, C. ,2012. “Using inertial sensors of iPhone 4 for car navigation”, Paper presented at the Position Location and Navigation Symposium (PLANS), 2012 IEEE/ION. Pan, J., & Tompkins, W. J. ,1985. “A real-time QRS detection algorithm”, Biomedical Engineering, IEEE Transactions on(3), 230-236. Pratama, A. R., & Hidayat, R. ,2012, ”Smartphone-based pedestrian dead reckoning as an indoor positioning system. Paper presented at the System Engineering and Technology (ICSET)”, 2012 International Conference on.Renaudin, V., Susi, M., & Lachapelle, G. ,2012, ” Step length estimation using handheld inertial sensors”,Sensors (Basel), 12(7):8507-8525.Schafer, R. W. ,2011,” What Is a Savitzky-Golay Filter?”, [Lecture Notes]. Signal Processing Magazine, IEEE, 28(4):111 - 117. Seco, F., Prieto, C., & Guevara, J. ,2009, ” A comparison of pedestrian dead-reckoning algorithms using a low-cost MEMS IMU”, Paper presented at the Intelligent Signal Processing, 2009. WISP 2009. IEEE International Symposium on. Shih, W.-Y., Chen, L.-Y., & Lan, K.-C. ,2012, ” Estimating walking distance with a smart phone”, Paper presented at the Parallel Architectures, Algorithms and Programming (PAAP), 2012 Fifth International Symposium on. Shin, S., Park, C., Kim, J., Hong, H., & Lee, J. ,2007, “ Adaptive step length estimation algorithm using low-cost MEMS inertial sensors”, Paper presented at the Sensors Applications Symposium, 2007. SAS`07. IEEE. Weinberg, H. ,2002, “ Using the ADXL202 in pedometer and personal navigation applications”, Analog Devices AN-602 application note. Weston, J., & Titterton, D. ,2000, “ Modern inertial navigation technology and its application”, Electronics & Communication Engineering Journal, 12(2):49-64. Yang, X., & Huang, B. ,2015, ” An accurate step detection algorithm using unconstrained smartphones”, Paper presented at the Control and Decision Conference (CCDC), 2015 27th Chinese. 描述 碩士
國立政治大學
地政學系
103257027資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103257027 資料類型 thesis dc.contributor.advisor 甯方璽 zh_TW dc.contributor.advisor Ning, Fang Shii en_US dc.contributor.author (作者) 吳東旂 zh_TW dc.contributor.author (作者) Wu, Dong Chi en_US dc.creator (作者) 吳東旂 zh_TW dc.creator (作者) Wu, Dong Chi en_US dc.date (日期) 2016 en_US dc.date.accessioned 2-九月-2016 00:51:39 (UTC+8) - dc.date.available 2-九月-2016 00:51:39 (UTC+8) - dc.date.issued (上傳時間) 2-九月-2016 00:51:39 (UTC+8) - dc.identifier (其他 識別碼) G0103257027 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/101171 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 地政學系 zh_TW dc.description (描述) 103257027 zh_TW dc.description.abstract (摘要) 隨著智慧型行動裝置及導航定位科技的快速發展，導航定位已成為目前日常生活上不可或缺的工具，室外的導航定位可以利用全球導航衛星系統(Global Navigation Satellite System, GNSS)導航訊號進行，但是室內定位部分由於訊號遮蔽，導致無法接收GNSS訊號進行導航定位，因此室內定位的各類方式應運而生，如Wireless、藍芽、無線射頻技術(Radio Frequency IDentification，RFID)、iBeacon等。每種不同的室內定位方式有不同的使用成本，使用成本直接影響室內定位方法的使用門檻。因此本研究透過使用行動裝置之微機電系統(Micro Electro Mechanical Systems，MEMS)獲取陀螺儀與加速度儀資訊，並且經由濾波器平滑訊號後偵測行走步伐，再透過最小二乘擬合方式進行步距估計，以行人航位推算(Pedestrian Dead Reckoning，PDR)方式求得位置坐標，另外亦透過場景建置地圖，依計算所得坐標與參考點之方位角與轉彎特徵尋找來判斷坐標校正時機，並將坐標校正為該時間坐標之相對正確位置。本研究結果顯示使用Savitzky-Golay Filter有助於提升步伐偵測準確性，且透過方位角計算的判斷依據與轉彎特徵判斷可以有效提升定位精度，於先期驗證中閉合差約為2.352公尺，後期驗證閉合差可達0.99公尺。 zh_TW dc.description.abstract (摘要) The widespread adoption of mobile device has improved the accuracy of navigation and location. Since nowadays Global Navigation Satellite System (GNSS) is easier to be installed in the mobile device to locate and navigate in the outdoors. Signals of GNSS are obstructed so navigation and positioning would be hard task to be executed indoors. Hence, methods of indoor positioning appear as the instruments of Bluetooth, RFID, IBeacon etc. Every method of indoor positioning has its respective cost to affect the selection of indoor positioning technique. In this study, uses data of gyroscope and accelerometer from Micro Electro Mechanical Systems (MEMS) and detects footsteps by using filter to smooth the signal, and then estimate the step length by the ordinary least square. Finally, use Pedestrian Dead Reckoning (PDR) to compute coordinates and use azimuth and the feature of turning to decide time of adjusting position. The results of this study show using the Savitzky-Golay Filter detecting footsteps and applying azimuths and turning feature adjusting coordinate can get the closure of the early test trial for 2.352m and in the post-test scene, the closure can be improved to 0.99m. en_US dc.description.tableofcontents 第一章 緒論 1第一節 研究背景與動機 1第二節 研究目的 3第三節 論文架構 4第二章 文獻回顧 5第一節 Android 系統 5一、Android 系統架構 5二、Android Activity 生命週期 6第二節 慣性導航系統 9一、加速度儀 9二、陀螺儀 10第三節 行人航位推算 12一、步長估計 14二、步伐偵測 19第四節 室內定位校正 23第五節 地圖匹配 26第三章 研究方法 33第一節 微機電系統資料獲取 35第二節 數據前處理 38一、加速度儀數據處理 38二、陀螺儀數據處理 42第三節 步長估計 45一、建立複迴歸模型 45二、模型驗證與分析 47第四節 步伐偵測 49第五節 坐標計算與位置校正 51ㄧ、先期測試 52二、後期測試 53第四章實驗成果與分析 61第一節 步伐偵測實驗 61第二節 步長估計實驗 66第三節 坐標計算與校正實驗 72ㄧ、先期測試之坐標計算與校正 72二、後期測試之坐標計算與校正 76第五章結論與建議 83第一節 結論 83第二節 建議 85參考文獻 87附錄 91 zh_TW dc.format.extent 4648514 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103257027 en_US dc.subject (關鍵詞) 室內定位 zh_TW dc.subject (關鍵詞) 行人航位推算 zh_TW dc.subject (關鍵詞) Savitzky-Golay Filter zh_TW dc.subject (關鍵詞) 場景約制 zh_TW dc.subject (關鍵詞) Indoor position en_US dc.subject (關鍵詞) Pedestrian Dead Reckoning en_US dc.subject (關鍵詞) Savitzky-Golay Filter en_US dc.subject (關鍵詞) Scene Constraint en_US dc.title (題名) 利用智慧型行動裝置與場景約制進行室內導航定位之研究 zh_TW dc.title (題名) Using Smart Mobile Device for Indoor Navigation with Scene Constraint en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 中文參考文獻王冬暉、許占文，「一種基於類投影的地圖匹配算法」，『瀋陽工業大學學報』，25(5):433-436。 王敏、魏衡華、鮑遠律，2012，「GPS導航系統中的地圖匹配算法」，『計算機工程』，38(14):259-261。 王楠、王勇峰，1999，「一種基於位置點匹配的地圖匹配算法」，『東北大學學報:自然科學板』，20(4):344-347。 江凱偉，2005，「空間定位技術發展之現況及未來展望」，『國土資訊系統通訊』，56。曲衍旭、郭倫嘉、張聖安、薛毓弘、馮堃齊、黃義雄，2012，「一結合無線訊號強度與慣性元件進行跨裝置間定位的系統與方法」，『電腦與通訊』，143:43-48。 李金鳳、王慶輝、劉曉梅，曹順、張慕遠,2014,「基於MEMS慣性傳感器的行人航位推算系統」，『傳感器與微系統』，33(12):85-87。 李清泉、黃練，「基於GPS軌跡數據的地圖匹配算法」，『測繪學報』，39(2):207-212。 林惠玲、陳正倉，2002，『應用統計學』四版修訂版，台北:雙葉書廊有限公司。 祁忠勇，1994，『FFT與訊號處理簡介』，演講紀錄。 姜仁傑、高永威、馮堃齊、陳威寧、林念真、林宛蓉，2014，「具多姿態步距校正之室內定位系統」，『電腦與通訊』，157:21-28。 柳林，2007，「移動終端導航系統中地圖匹配技術的研究與應用」，山東科技大學地圖製圖學與地理信息工程專業博士論文:山東 胡安東、王堅、高井祥，2014，「一種基於地圖匹配輔助行人航位推算的室內定位方法」，『測繪科學技術學報』，31(5):529—532。 陳會安，2015，「新觀念 Android程式設計範例教本 使用Android Studio」，台北，旗標出版股份有限公司。 彭威然，2014，「使用手機加速度計和陀螺儀之室內定位」，淡江大學資訊工程學系網路與通訊碩士班學位論文:新北。 楊凡、趙東東，2012，「基於 Android平台的WiFi定位」，『電子側量技術』，35(9):116-119。 楊東凱、寇艷紅、吳金培、張其善，2003，「智能交通系统中的地图匹配定位方法」，『交通運輸系統工程與信息』，3(3):38-43。 英文參考文獻Attia, M., Moussa, A., & El-Sheimy, N., 2013, “Map aided pedestrian dead reckoning using buildings information for indoor navigation applications”, Positioning. Beauregard, S.,Haas, H. ,2006, ”Pedestrian dead reckoning: A basis for personal positioning”. Paper presented at the Proceedings of the 3rd Workshop on Positioning, Navigation and Communication. Beauregard, S., Klepal, M.,2008, “Indoor PDR performance enhancement using minimal map information and particle filters”, Position, Location and Navigation Symposium ,2008 IEEE/ION. IEEE, 2008. 141-147. Bullock, J. ,Krakiwsky, E. ,1994,” Analysis of the use of digital road maps in vehicle navigation”. Position Location and Navigation Symposium, IEEE. Chen, G., Meng, X., Wang, Y., Zhang, Y., Tian, P., & Yang, H.,2015,” Integrated WiFi/PDR/Smartphone Using an Unscented Kalman Filter Algorithm for 3D Indoor Localization”,Sensors,15(9):24595-24614. Gilliéron, P. Y., Büchel, D., Spassov, I., & Merminod, B., 2004, “ Indoor navigation performance analysis”, ENC GNSS, 30. Goyal, P., Ribeiro, V. J., Saran, H., & Kumar, A., 2011, “Strap-down pedestrian dead-reckoning system”, measurements , 2:3. Groves, P. D., 2013, 『Principles of GNSS, inertial, and multisensor integrated navigation systems』, Artech house.Grove, P.D., “Principles of Integrated Navigation,” Course Notes, QinetiQ Ltd., 2002. Koifman, M., & Bar-Itzhack, I., 1999, “Inertial navigation system aided by aircraft dynamics”, Control Systems Technology, IEEE Transactions on, 7(4):487-493. Kroger, T., Chen, Y., Pei, L., Tenhunen, T., Kuusniemi, H., Chen, R., & Chen, W., 2010, “Method of pedestrian dead reckoning using speed recognition.”, Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), 1-8.Liu, Y., Chen, Y., Shi, L., Tian, Z., Zhou, M., & Li, L., 2015, “Accelerometer Based Joint Step Detection and Adaptive Step Length Estimation Algorithm Using Handheld Devices”, Journal of Communications, 10(7). Marschollek, M., Goevercin, M., Wolf, K.-H., Song, B., Gietzelt, M., Haux, R., & Steinhagen-Thiessen, E. ,2008,.” A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons”. Paper presented at the Engineering in Medicine and Biology Society. ,30th Annual International Conference of the IEEE. Niu, X., Zhang, Q., Li, Y., Cheng, Y., & Shi, C. ,2012. “Using inertial sensors of iPhone 4 for car navigation”, Paper presented at the Position Location and Navigation Symposium (PLANS), 2012 IEEE/ION. Pan, J., & Tompkins, W. J. ,1985. “A real-time QRS detection algorithm”, Biomedical Engineering, IEEE Transactions on(3), 230-236. Pratama, A. R., & Hidayat, R. ,2012, ”Smartphone-based pedestrian dead reckoning as an indoor positioning system. Paper presented at the System Engineering and Technology (ICSET)”, 2012 International Conference on.Renaudin, V., Susi, M., & Lachapelle, G. ,2012, ” Step length estimation using handheld inertial sensors”,Sensors (Basel), 12(7):8507-8525.Schafer, R. W. ,2011,” What Is a Savitzky-Golay Filter?”, [Lecture Notes]. Signal Processing Magazine, IEEE, 28(4):111 - 117. Seco, F., Prieto, C., & Guevara, J. ,2009, ” A comparison of pedestrian dead-reckoning algorithms using a low-cost MEMS IMU”, Paper presented at the Intelligent Signal Processing, 2009. WISP 2009. IEEE International Symposium on. Shih, W.-Y., Chen, L.-Y., & Lan, K.-C. ,2012, ” Estimating walking distance with a smart phone”, Paper presented at the Parallel Architectures, Algorithms and Programming (PAAP), 2012 Fifth International Symposium on. Shin, S., Park, C., Kim, J., Hong, H., & Lee, J. ,2007, “ Adaptive step length estimation algorithm using low-cost MEMS inertial sensors”, Paper presented at the Sensors Applications Symposium, 2007. SAS`07. IEEE. Weinberg, H. ,2002, “ Using the ADXL202 in pedometer and personal navigation applications”, Analog Devices AN-602 application note. Weston, J., & Titterton, D. ,2000, “ Modern inertial navigation technology and its application”, Electronics & Communication Engineering Journal, 12(2):49-64. Yang, X., & Huang, B. ,2015, ” An accurate step detection algorithm using unconstrained smartphones”, Paper presented at the Control and Decision Conference (CCDC), 2015 27th Chinese. zh_TW
