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系統識別號 U0026-2108201801172000
論文名稱(中文) 鳳凰立方衛星入軌後之磁力計校正
論文名稱(英文) In-Flight Magnetometer Calibration with Temperature Compensation for PHOENIX CubeSat
校院名稱 成功大學
系所名稱(中) 電機工程學系
系所名稱(英) Department of Electrical Engineering
學年度 106
學期 2
出版年 107
研究生(中文) 洪銘陽
研究生(英文) Ming-Yang Hong
電子信箱 hmi60117@gmail.com
學號 N26054257
學位類別 碩士
語文別 英文
論文頁數 82頁
口試委員 指導教授-莊智清
口試委員-苗君易
口試委員-壽鶴年
口試委員-余國瑞
口試委員-李佩君
中文關鍵字 立方衛星  磁力計校正  溫度補償  姿態控制與估測  粒子群最佳演算法 
英文關鍵字 CubeSat  In-Flight Magnetometer Calibration  Temperature Compensation  Attitude Control and Determination  Particle Swarm Optimization 
學科別分類
中文摘要 歐盟QB50計畫之一的鳳凰(PHOENIX)為一枚兩單位大小之立方衛星,由國立成功大學設計、組裝整合、測試,且於2017年五月中旬從國際大空站釋放至低地球軌道(高度約400公里)並成功與成大地面站通聯,而入軌操作至今,磁力計校正被視為一項重要的例行任務,而校正效果影響姿態控制與估測的準確性,然而,由於鳳凰立方衛星之磁力計缺少溫度補償之機制,三軸磁力計量測自然地受到繞軌之溫度變化影響,而磁力計之準確度大大影響著衛星姿態控制與估測之效能,基於此動機與目的,本論文主要研究磁力計校正與溫度補償之關係,並且,研究找出對於無溫度補償之磁力計,溫度相依性質影響較小之校正參數。
此研究透過粒子群最佳演算法,根據擴展後之三軸磁力計量測誤差數學模型,找出12個最佳之磁力計校正參數,其中包含三軸偏差值、比例因子、非正交性項以及前述項所對應之溫度相關係數,接著,磁力計校正之驗證藉由實際入軌之鳳凰立方衛星作為實驗平台,收集多次繞軌之磁力計與相關資料並且更新上傳校正後之參數,以驗證本研究之磁力計校正的準確性與粒子群最佳演算法收斂之可靠性。
英文摘要 PHOENIX is a 2U CubeSat in the QB50 project that is designed, assembled, integrated, tested and operated by National Cheng Kung University, Taiwan. After the deployment from International Space Station (ISS) in May 2017, extensive studies on magnetometer calibration have been conducted. The performance of attitude determination and control subsystem (ADCS) for PHOENIX depends on the reliability and accuracy of magnetometer calibration.
The thesis is concerned with the in-flight magnetometer calibration which will be naturally influenced by the variation of temperature during the course of orbiting around the earth. A temperature-dependent magnetometer model is proposed and a particle swarm optimization method is adopted in the estimate of calibration parameters. The proposed model and method are verified and tested by using in-flight data from PHOENIX. It has shown that the use of the proposed model together with the optimization method renders a closer match between the magnitudes of the measurement vector and IGRF model. Additionally, the calibration method can be extended to find the suboptimal solution for the satellites with magnetometers without the mechanism of temperature compensation. The proposed approach is believed to be beneficial for small satellites and CubeSats that rely on the use of magnetometer data for attitude determination, orbit determination, and attitude control.
論文目次 摘要 I
Abstract II
Acknowledgements IV
Contents V
List of Tables VIII
List of Figures IX
List of Abbreviations XI
Chapter 1 Introduction 1
1.1 Motivation and Objectives 1
1.2 Overview of PHOENIX Mission 2
1.2.1 QB50 Mission 2
1.2.2 Overview of PHOENIX 5
1.3 Thesis Overview 8
Chapter 2 PHOENIX ADCS 9
2.1 Attitude Determination and Control Subsystem 9
2.1.1 Coordination Definition 9
2.1.2 ADCS Module Specification 10
2.1.3 Control and Estimation Modes 12
2.2 In-Flight ADCS Experience 14
2.2.1 High Rate Detumbling 14
2.2.2 Y-Spin Control 16
2.2.3 Y-momentum Control 18
Chapter 3 In-Flight TAM Calibration Methods 21
3.1 Mathematical Model of Magnetometer 21
3.1.1 External Errors 21
3.1.2 Internal Errors 22
3.1.3 Measurement Model of 3-Axis Magnetometer 25
3.2 Review of Existing Calibration Methods 28
3.2.1 Least Square Method 28
3.2.2 TWOSTEP Algorithm 29
3.2.3 Nonlinear-Kalman-Filter Based Algorithm 31
3.2.4 Particle Swarm Optimization 32
3.3 PSO-Based Magnetometer Calibration 32
3.3.1 Particles Initialization 33
3.3.2 Particles Evaluation 34
3.3.3 Particles Update 34
Chapter 4 In-Flight TAM Calibration and Verification 37
4.1 Background 37
4.1.1 3-Axis Magnetometer of PHOENIX 37
4.1.2 Thermometers of PHOENIX 39
4.1.3 IGRF Model 41
4.1.4 In-Flight Data Collection 43
4.2 Ground-Calibration with In-Flight Data 45
4.2.1 CubeSupport Calibration 45
4.2.2 PSO-Based Calibration 46
4.2.2.1 Initial Parameters Setting 47
4.2.2.2 Comparison Test 49
4.2.2.3 Results of PSO-Based Calibration 49
4.3 In-Flight Test of Calibrated Parameters 59
4.4 Further Study of Magnetometer Calibration 63
4.4.1 The Setting of Temperature Reference T0 63
4.4.1.1 Comparison with Results from CubeSupport 65
4.4.2 Analysis of PSO-Based Calibration 68
4.4.2.1 Different Setting of Initial Boundary 68
4.4.2.2 Dynamic Weighting Parameters 71
Chapter 5 Conclusions and Future Works 74
5.1 Discussions 74
5.2 Future Works 76
References 79
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