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系統識別號 U0026-0608201412274500
論文名稱(中文) 移動式車載重力測量之研究
論文名稱(英文) The study of moving base INS/GNSS gravimetry on a land vehicle
校院名稱 成功大學
系所名稱(中) 測量及空間資訊學系
系所名稱(英) Department of Geomatics
學年度 102
學期 2
出版年 103
研究生(中文) 古伊庭
研究生(英文) I-Ting Ku
學號 P66014109
學位類別 碩士
語文別 英文
論文頁數 106頁
口試委員 指導教授-江凱偉
共同指導教授-郭重言
口試委員-蕭宇伸
中文關鍵字 重力擾動  SINS/GNSS 整合  GNSS 加速度 
英文關鍵字 Moving-base gravimetry  gravity disturbance  SINS/GNSS integration  GNSS acceleration 
學科別分類
中文摘要 傳統重力測量利用重力儀量測特定點的重力值,需要很多人力而且耗時,為了克服這些缺點,更方便測得重力,其他形式的重力測量慢慢發展,例如車載、船載、空載重力測量。車載移動式SINS/GNSS整合系統與傳統重力儀相比,比較有效率,人力和花費也都較省,而與空載重力測量相比,車載移動式整合系統可以提供高精度與較小空間解析度的重力場資訊。此外,這些重力資料可以應用在其他科學研究,例如決定大地水準面、調查造山運動、研究海底構造、質量不平衡的地方等等。
在本研究中使用儀器包括一個導航等級的IMU搭配GNSS接收儀。導航等級IMU中,陀螺儀和加速度計的偏差分別小於0.002deg/h 和10ug (戰術等級的IMU,陀螺儀和加速度計的偏差分別小於0.1deg/h和100ug)。本研究規劃了兩個實驗,一個是收集台南到泰安休息站的高速公路的資料,另一個則是從仁德出發,沿著國道一號→快速道路82→國道三號→快速道路86的路線繞一圈,最後回到仁德,同一路線會重複跑兩到三次,因此我們可以針對重力資訊的重複性作分析。實驗分成靜態及動態兩種模式。靜態測量時,車子沿路會停五分鐘作ZUPT,利用ZUPT的資料來檢驗GNSS算出來的加速度以及重力擾動是否合理,目前靜態重力資料的精度可在10mgal內。動態資料中還無法求得合理重力擾動值,所以希望未來可以藉由訊號處理技術得到改善。
英文摘要 Gravity is traditionally measured by land gravimeter; however, it is time and labor consuming. In order to overcome this deficiency and measure gravity conveniently, vehicle, airborne or ship gravimetry are developed, but nowadays these equipments are still very expensive and lack operational efficiency. Compared to traditional methods using gravimeters, a moving base gravimetry system, composed of a SINS/GNSS integrated system by mounting on land vehicle is relatively efficient, labor and cost saving. Compared to airborne gravimetry, it also could provide highly accurate, high spatial resolution and local gravity signals. Besides, The SINS/GNSS derived gravity can be used to study scientific topics; for example, determining geoid, investigating orogeny, study sea floor structure, hydrology, mass inbalance.
The systems applied in this study include a navigation grade IMU with gyro and accelerometers biases less than 0.002deg/h and 10ug and GNSS receiver. In our study, there are two experiments for the plain area. The first one was carried out along the highway from Tainan to Taian. The second one started from Rende along the highway (National Freeway No.1→ Expressway 82→National Freeway No.3→ Expressway 86) and back to Rende in western Taiwan. The routes were repeated more than once. Therefore, we could analyze the quality of our gravity estimates in terms of repeatability. The capability of the IMU for gravimetry was tested in the static and kinematic mode, respectively. In the static mode, the car was stopped five minutes every stopping point to perform ZUPT. We can check if the GNSS acceleration and gravity disturbance are good or not. The estimated gravity accuracy is at the level of 10mGal, which indicates good applicability of the unit for geodetic purposes. In kinematic mode, the gravity disturbances have not reached a reasonable value until now. Therefore, we hoped it could be improved in the future work.
論文目次 Table of Contents
中文摘要 I
Abstract II
Acknowledgments IV
Table of Contents V
List of Tables VIII
List of Figures X
Glossary of acronyms XII

Chapter 1 Introduction 1
1.1 Background and motivation 1
1.2 Literature Review 4
1.3 Thesis Outline 8
Chapter 2 GNSS/INS Integrated System 9
2.1 Coordinate frames and transformations 9
2.1.1 Inertial frame (i-frame) 9
2.1.2 Earth-centered Earth-fixed frame (e-frame) 10
2.1.3 Navigation frame (n-frame) 10
2.1.4 Body frame (b-frame) 12
2.2 Global Navigation Satellite System (GNSS) 14
2.2.1 GNSS Structure 15
2.2.2 GNSS observables and errors 19
2.2.3 DGNSS 22
2.3 Inertial Navigation System 24
2.3.1 Physical implement of IMU 25
2.3.2 INS mechanization equations 26
2.3.3 INS error equations 30
2.4 Multi-sensor Integrated algorithm 33
2.4.1 Kalman filter 34
2.4.2 Smoothing 37
Chapter 3 SINS/DGNSS Gravimetry 39
3.1 SINS/DGNSS gravimetry 39
3.2 Airborne gravimetry 41
3.2.1 Gravity anomaly 43
3.2.2 Gravity disturbance 44
3.2.3 The Computational methodology for inertial gravimetry 45
3.3 GNSS kinematic acceleration 47
3.3.1 Numerical differential method 48
3.3.2 Filter processing 49
3.4 Data Processing 49
Chapter 4 Experiments and Results 51
4.1 System setup and survey campaign 51
4.1.1 Experiment 1 (test) 51
4.1.2 Hardware 52
4.1.3 Software 54
4.2 Static IMU gravimetry 55
4.2.1 IMU data processing 56
4.2.2 The determination of IMU data processing strategy 61
4.3 Experiment 2 63
4.3.1 IE results: DGNSS (Only) and DGNSS/INS data 66
4.3.2 RTK library results: DGNSS data (Only) 71
4.3.3 Comparison between IE and RTK library data 74
4.3.4 Spatial resolution 80
4.4 The analysis of GNSS filter 82
4.4.1 Different window size of Gaussian filter 82
4.4.2 Different order of Butterworth filter 85
4.4.3 Different fc of Butterworth filter 86
4.5 IMU acceleration (specific force) 87
4.6 Gavity disturbance 88
4.6.1 Gavity disturbance 88
4.6.2 Repeatability 91
4.6.3 Box plot 96
4.7 Statistical hypothesis 98
4.7.1 Statistical hypothesis-Gravity disturbance 99
4.7.2 Statistical hypothesis- GNSS acceleration 100
Chapter 5 Conclusions and future work 101
5.1 Conclusions 101
5.2 Future work 102
References 103

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