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研究生: 楊先立
Yang, Hsien-Li
論文名稱: 緊密式耦合演算法在整合式北斗衛星與慣性導航之研究
Research on Tightly Coupled Algorithm in Integrated BeiDou and Inertial Navigation System
指導教授: 莊智清
Juang, Jyh-Ching
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年: 2016
畢業學年度: 104
語文別: 英文
論文頁數: 70
中文關鍵詞: 卡爾曼濾波器緊密式耦合慣性導航衛星導航
外文關鍵詞: Kalman filter, tightly coupled, inertial navigation, satellite navigation
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  • 時至今日,全球定位系統 (GPS) 已經發展完全,並廣泛應用在許多領域,車輛、軍事、導航、航空及航太都能看到GPS。其應用在生活中隨處可見,我們仰賴GPS去許多地方。不過在市區的環境,GPS常常被建築物、隧道等障礙遮蔽信號,或是產生多路徑效應、週波脫落等現象。
    為了處理這些問題,我們使用慣性導航系統 (INS) 做輔助,INS的優點為高更新率、不易受外界干擾、短時間高精確度等優點。我們常用擴展式卡爾曼濾波器 (EKF) 以整合GPS和INS的系統。根據GPS和INS得到的載具運動資訊,我們能計算出載具的位置、速度和姿態。
    北斗衛星系統 (BDS) 由中國開發,包含35個衛星,其中五個為同步軌道衛星、3個傾斜同步軌道衛星和27個中地球軌道衛星,我們結合北斗系統和GPS系統,並用EKF整合進INS,幫助我們有更準確的定位。
    常見的GPS/INS 整合式系統具有諸多優點,精確姿態、高取樣率、訊號不怕中斷、長時間有穩定精確度….等,考慮到引進不同的衛星系統不僅能觀測更多衛星,在天球上衛星的幾何分布也會改善,因此本論文探討將北斗衛星系統、GPS、以及INS整合的功效。
    關鍵字: 卡爾曼濾波器、緊密式耦合、慣性導航、衛星導航

    Nowadays, Global Positioning System (GPS) which has been developed completely are widely used in various fields, such as vehicle, military, navigation, airplane and spacecraft. Applications of GPS are everywhere in our life, and we rely on GPS for route guidance. However, in urban environment, GPS signals are sometimes blocked by buildings, tunnels, or affected by multipath effect.
    To deal with this problem, we can employ the inertial navigation system (INS). This system have advantages such as high updating rate, not easily affected by external interference, and high accuracy in short time. We usually use an extended Kalman filter (EKF) to integrate GPS and INS. According to the information of motion measured from INS and GPS, we can estimate the velocity, position, and attitude of the vehicle.
    BeiDou satellites system (BDS) is developed by China. This system is composed of 35 satellites, including 5 geostationary orbit satellites, 27 in medium Earth orbit, and 3 in inclined geosynchronous orbit. We want to combine BDS into our system with GPS and INS, helping us to achieve higher accuracy.
    The GPS/INS integration system has many advantages, such as accurate attitude, high sampling rate, continuously signals, and accuracy along time and so on. By combining others satellite systems can not only observe more satellites, but also get better geographic distribution of satellites in the sky. The thesis discussed the integrations of Beidou, GPS, and INS to seek performance enhancement.
    Keyword: Kalman filter; tightly coupled; inertial navigation; satellite navigation.

    Content 摘要 I ABSTRACT II ACKNOWLEDGEMENT IV CONTENT V LIST OF TABLES VIII LIST OF FIGURES IX CHAPTER 1 INTRODUCTION - 1 - 1.1 Motivation - 1 - 1.2 Background - 2 - 1.3 Organization - 3 - CHAPTER 2 INERTIAL NAVIGATION SYSTEM - 4 - 2.1 Coordinate system - 4 - 2.1.1 Earth-Centered Inertial Frame (ECI) - 4 - 2.1.2 Earth-Centered Earth-Fixed Frame (ECEF) - 5 - 2.1.3 Local level frame (navigation frame) - 6 - 2.1.4 Vehicle frame (Body frame) - 8 - 2.1.5 Sensor frame - 8 - 2.2 Transformation of coordinate frames - 9 - 2.2.1 Rotation matrix - 9 - 2.2.2 ECI to ECEF - 10 - 2.2.3 ECEF to Local level frame - 10 - 2.2.4 Local level frame to body frame - 11 - 2.3 Inertial navigation system (INS) - 12 - 2.3.1 Introduction of inertial navigation - 12 - 2.3.2 Classification of INS - 13 - 2.4 Inertial measurements unit error analysis - 16 - CHAPTER 3 GPS/BEIDOU/INS INTEGRATION SYSTEM - 20 - 3.1 Introduction of GPS - 20 - Composition of GPS - 20 - Positioning Principle - 21 - 3.2 Algorithm of GPS positioning - 22 - 3.3 Introduction of Beidou satellite system - 25 - Coordinate system - 25 - Time system - 26 - Frequency band - 26 - Positioning method - 26 - 3.4 Integrated navigation system - 27 - 3.4.1 GPS/INS integration system - 28 - 3.4.2 Uncoupled - 29 - 3.4.3 Loosely coupled - 30 - 3.4.4 Tightly coupled - 31 - 3.4.5 Ultra tightly coupled - 32 - 3.5 Kalman filter - 33 - 3.6 Integrated GPS/BDS/INS via Kalman filter - 37 - 3.6.1 Extended Kalman filter - 37 - 3.6.2 Dynamic correction of sensor - 39 - 3.6.3 Practical application of extended Kalman filter - 40 - CHAPTER 4 EXPERIMENT RESULT AND ANALYSIS - 47 - 4.1 Static positioning test - 47 - 4.2 Road testing in urban area - 48 - 4.2.1 Least squares method - 50 - 4.2.2 Inertial navigation system simulation - 53 - 4.3 Integrated system with tightly coupled algorithm - 58 - 4.3.1 GPS/INS integration system - 58 - 4.3.2 Beidou/INS integration system - 63 - CHAPTER 5 CONCLUSIONS AND FUTURE WORK - 68 - 5.1 Conclusions - 68 - 5.2 Future work - 68 - REFERENCE: - 69 -

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