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研究生： 朱建勲
Chu, Chien-Hsun
論文名稱： 提升陸、空移動製圖系統之定位精度輔助演算法
The Development Of Aiding Algorithms To Improve The Positioning Accuracy Of Land Based And Airborne Mobile Mapping Systems
指導教授： 江凱偉
Chiang, Kai-Wei
學位類別： 博士
Doctor
系所名稱： 工學院 - 測量及空間資訊學系
Department of Geomatics
論文出版年： 2016
畢業學年度： 105
語文別： 英文
論文頁數： 175
中文關鍵詞： 空間資訊 、移動製圖 、定位定向
外文關鍵詞： Mobile Mapping System, Calibration, Positioning and Orientation System
相關次數： 點閱：169  下載：11 
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    • 現有空間資訊系統之效益建構在系統空間及屬性資料時效性以及正確性，並藉此發揮它的功能以表示真實世界的現象。測量技術及屬性調查日新月異，由地面經緯儀點的量測至空中攝影測量面狀量測，由人工繪圖及文字描述至影像紀錄，但是從開始收集資料至成果獲得仍然往往需半年以上，對於高頻率的更新稍顯不足。自1990年起，加拿大及美國結合高精度整合式定位定向技術及攝影測量製圖技術，發展地面、空中移動製圖技術，移動製圖技術除了大幅減少外業作業量，而提升資料更新率，更可結合地面及空中多方向的拍攝紀錄完整的空間資訊。現今，移動製圖技術已被大量利用在軍事、民生、科學、商業、防災、監測及國土規劃等空間資訊收集。雖然移動製圖技術大幅提升資料更新率及完整性，但是對於精度部分能存在缺陷。
    國立成功大學測量及空間資訊學系，自2008年起開始自主發展車載及空載移動製圖技術。本論文接續發展，除詳細剖析移動製圖技術，更發展具實用性軟、硬體及作業模式，並針對存在的問題持續精進，包含提出混合式定位定向解算法以提升定位定向解及動態率定預估時間延遲。更進一步的，本論文也發展推車式移動製圖技術，可於室內環境收集資料，更提出控制點反饋於室內環境保持精度。本論文針對提出的演算法進行相關的作業測試，對於混合式演算法測試，於理想環境下，提供三維絕對精度約50公分的車載移動製圖系統。對於動態率定測試，於航高300公尺，提供三維絕對精度8公尺的空載無人飛行機移動製圖系統。對於控制點反饋，於室內環境，提供三維絕對精度70公分的手推車式室內移動製圖系統。未來空間資訊，除了結合多平台移動製圖技術資訊而保持全面性外，將朝高精度的三維定位和高解析度的資料，以保持細緻性及大量資料處理的自動性進步。

    The efficiency and advantages of spatial information systems rely on the validity and time effectiveness of spatial and attribute information to work properly and express the real world phenomenon. Surveying and attribution inventory technologies have quickly improved. Surveying technology advanced from surveying point using total station on the ground to surveying plan using aero photogrammetry in air, and attribution inventory developed from manual drawing to image record. However, high-frequency update is necessary because it usually requires about half a year of collecting data to provide the product. Since 1990, Canada and the United States have developed land and aero Mobile Mapping Systems (MMS) for solving this problem, which combine the high-accuracy Positioning and Orientation System (POS) and photogrammetry technology. MMS technologies not only decrease outdoor work for efficiency but also record complete spatial information by combining multi-directional photos from land and air. Currently, MMS technologies are applied in the military, livelihood, science, business, disaster prevention, monitoring, and land planning. Although MMS technologies improve data update frequency and integrity, its accuracy remains weak.
    The Department of Geomatics in National Cheng Kung University has developed a land MMS van and aero MMS since 2008. This thesis continues this work not only by introducing the details of MMS technologies but also by developing a more practical software, hardware, and process mode. Furthermore, this thesis proposes Hybrid Tightly Coupled (HTC) for improving accuracy and kinematic calibration to estimate the time delay problem. A portable MMS cart for indoor environment is also developed, and Control Point Feedback (CPF) for improving accuracy indoors is proposed. Relative experiments are conducted to verify these proposed methods. To confirm HTC, this thesis produces 3D absolute accuracy of 50 cm of land MMS in an ideal outdoor environment. To confirm kinematic calibration, this thesis produces 3D absolute accuracy of 8 m of Unmanned Aircraft Vehicle (UAV) MMS with 300 flight height. To verify CPF, this thesis produces 3D absolute accuracy of 70 cm of land MMS cart in an indoor environment. In the future, MMS technologies will not only maintain the comprehensiveness of spatial information but will also require improve positioning accuracy in 3D and data resolution to keep the meticulous content and automatically process a large quantity of data.

    TABLES OF CONTENT 摘要 I ABSTRACT II ACKNOWLEDGMENTS IV TABLES OF CONTENT V GLOSSARY OF ACRONYMS VIII LIST OF TABLES X LIST OF FIGURES XIV Chapter 1. Introduction 1 1.1. Motivation 1 1.2. Problem Statements 2 1.3. Research Objective 5 1.4. Contributions 6 Chapter 2. Position and Orientation System 8 2.1 Inertial Navigation System 9 2.1.1. Sensor Error and Compensation 10 2.1.2. INS Mechanization 12 2.1.3. Integration of Velocity, Position, and Attitude 14 2.2. Global Navigation Satellite System 17 2.2.1. GNSS Observables 17 2.2.2. GNSS Measurement Processing Mode 19 2.3. Alignment Mode 24 2.4. INS and GNSS Integrated System 26 2.4.1. Kalman Filter 28 2.4.2. Extended Kalman Filter 30 2.5. Smoothing Algorithm 33 Chapter 3. Part of Photogrammetry 39 3.1. Collinearity 39 3.2. Bundle Adjustment 40 3.3. Intersection 43 3.4. Resection 44 Chapter 4. Direct Georeferencing 45 4.1. Direct Georeferencing 45 4.2. System Calibration 47 4.2.1. IMU Calibration 47 4.2.1. Camera Calibration 49 4.2.1. Direct Georeferencing Calibration 52 4.3. Error Source 59 Chapter 5. Proposed Algorithms 62 5.1. Proposed Algorithm 1: Hybrid Tightly Coupled Scheme 62 5.2. Proposed Algorithm 2: Kinematic Calibration 64 5.3. Proposed Algorithm 3: Control Point Feedback 67 Chapter 6. Experiments and Results 70 6.1. Pointer Software 70 6.2. Data Processing Strategy 72 6.3. Test 1: LMMS–HTC 75 6.3.1. Proposed LMMS 75 6.3.2. HTC Test 83 6.4. Test 2: AMMS–Kinematic Calibration 88 6.4.1. Proposed AMMS 89 6.4.2. Kinematic Calibration Test 93 6.4.3. Result and Analysis 95 6.5. Test 3: PMMS–CPF 102 6.5.1. Proposed PMMS 102 6.5.2. CPF 107 6.6. Conclusions 113 Chapter 7. Conclusions and Future Works 114 7.1. Conclusions 114 7.2. Future works 116 Appendix A - Fundamentals of MMS 121 Appendix B: EKF 141 References 153

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