Browse

Sensor Failure Scenarios and Corresponding Solutions of Three Axis Magnetometer Integrated GPS/INS UAV Navigation System
3축 지자기 센서 결합 GPS/INS 무인기 항법 시스템의 센서 고장 시나리오 및 대처 방안

DC Field Value Language
dc.contributor.advisor기창돈-
dc.contributor.authorHeekwon No-
dc.date.accessioned2017-07-13T06:29:50Z-
dc.date.available2017-07-13T06:29:50Z-
dc.date.issued2017-02-
dc.identifier.other000000141767-
dc.identifier.urihttp://hdl.handle.net/10371/118600-
dc.description학위논문 (박사)-- 서울대학교 대학원 : 기계항공공학부, 2017. 2. 기창돈.-
dc.description.abstractIn this thesis, measurement of 3-axis magnetometer is integrated with GPS/INS navigation system in order to improve the navigation performance and to solve the problem of performance degradation caused by sensor failure.
GPS/INS integrated navigation system is widely used as a small UAV navigation system. GPS/INS integrated navigation system has excellent navigation performance by combining stable navigation performance of GPS with high accuracy navigation performance of INS during a short time. However, the GPS/INS integrated navigation system cannot observe the attitude error in the static condition like horizontal straight flight, and it is impossible to observe the attitude error completely even when the maneuver such as linear acceleration or horizontal turning is performed. In order to compensate for this lack of observability, magnetometer is additionally integrated to the geomagnetic sensor. There are two methods of magnetometer integration: a magnetic heading integration method and magnetic vector integration method.
The magnetic heading integration method determines the heading from the magnetic field measurement, assuming that the roll angle and the pitch angle are known, and then integrates the heading information with the navigation system. On the other hand, the magnetic vector integration method doesn’t require the information about the roll angle and the pitch angle, and the attitude information of the two axes perpendicular to the magnetic vector is provided. However, the use of the magnetic vector integration method with inaccurate magnetic measurements may adversely affect navigation performance. Therefore, mainly the magnetic heading integration method have been widely used.
The factors that cause errors in the measurements of the magnetometer are the current flowing around the sensor and the influence of the metal located around the sensor. Small UAV mainly uses electric motors to drive the propeller. Therefore, electric currents that drive the motors to the electric wires connected between the battery and the electric motors cause errors in the magnetometer located around the electric wires. When the current sensor is installed and the measured current values are used, the magnetic field error of the bias type generated by the current can be compensated, but there is a problem that the noise of the magnetometer measurement value is increased due to the PWM driving current characteristic of the motor. In this thesis, a compensation method of the magnetic field error by combining the throttle input and the current measurement by deriving the relation between the throttle input and the motor drive current is proposed. This method is effectively compensating the measurement error of the bias and noise type geomagnetic sensor. A vector calibration method based on flight data is proposed as a method to compensate for magnetic field distortion caused by metal objects. This method precisely models the magnetic field distortion caused by the surrounding metal using the attitude information of the GPS/INS integrated navigation and the spherical harmonics model (SHM) and has superior performance compared to the scalar based calibration method such as the existing ellipsoid calibration method. In this way, magnetometer calibration methods suitable for small UAV is proposed, and these methods improve the accuracy and usability of the magnetometer measurements.
In this thesis, the magnetic vector integration is performed in the GPS/INS navigation system using the high accuracy magnetic field measurements through the proposed magnetometer calibration method. When GPS is available, the accuracy of the attitude is improved compared with the conventional magnetic heading integration method. In the case where GPS is not available, stability of the navigation system is improved by reducing divergence of velocity and position error as well as attitude error.
On the other hand, GPS/INS integrated navigation cannot be performed in case of IMU failure. Position and velocity information can be obtained from GPS receiver, but alternative systems for attitude estimation are required. In this thesis, attitude error of the single-antenna GPS attitude determination method is estimated by integrating 3-axis magnetometer. In addition, the performance of the alternative attitude estimation system is improved by subdividing the fault situation of the IMU and integrating the available measurements in each situation.
In this thesis, the failures of various sensors constituting a small UAV GPS/INS navigation system are assumed and the stability and survivability of the UAV are improved by reducing the performance degradation of the navigation system in each situation
-
dc.description.tableofcontentsCHAPTER 1. INTRODUCTION 1
1.1 MOTIVATION AND PURPOSE OF RESEARCH 1
1.2 PREVIOUS RESEARCH 3
1.3 CONTENTS AND METHOD OF RESEARCH 5
1.4 THESIS CONTRIBUTIONS 7
CHAPTER 2. UAV NAVIGATION SYSTEM 11
2.1 GLOBAL NAVIGATION SATELLITE SYSTEM (GNSS) 11
2.1.1 Configuration of GNSS 11
2.1.2 Measurement of GNSS Receiver 14
2.1.3 Principles and Characteristics of GNSS 15
2.1.4 Failure of GNSS 19
2.2 INERTIAL NAVIGATION SYSTEM (INS) 20
2.2.1 Configuration of INS 20
2.2.2 Principles and Characteristics of INS 21
2.2.3 Inertial Measurement Unit (IMU) and Measurement 23
2.2.4 Failure of INS 24
2.3 MAGNETOMETER 25
2.3.1 Magnetic Field of the Earth 25
2.3.2 AMR Magnetometer and Error Sources 29
2.4 GNSS/INSS INTEGRATED NAVIGATION SYSTEM 31
2.4.1 Characteristics of GNSS/INS Integration 31
2.4.2 Error Equation of INS 32
2.4.3 Loosely Coupled GNSS 37
2.4.4 Tightly coupled GNSS 38
2.4.5 Failure of GNSS/INS Integrated Navigation System 40
2.5 ATTITUDE ESTIMATION SYSTEM 41
2.5.1 Inertial Sensor Based Attitude Determination 41
2.5.2 GNSS Based Attitude Determination 43
2.5.3 Magnetometer Based Attitude Determination 44
CHAPTER 3. CALIBRATION OF MAGNETOMETER 46
3.1 INFLUENCE OF CURRENT AND COMPENSATION 46
3.1.1 Magnetic Field Generated by Current 46
3.1.2 Compensation of Magnetic Field Error Using Current Measurement 53
3.1.3 Compensation by Integrating Throttle Input and Current Measurement 58
3.2 INFLUENCE OF METAL AND CALIBRATION 68
3.2.1 Magnetic Field Distortion by Metal 68
3.2.2 Calibration Method Based on Ellipsoid 73
3.2.3 Calibration Method Based on Spherical Harmonics Model 75
3.2.4 SHM Calibration Method by Using Flight Data 77
3.3 MAGNETIC MEASUREMENT ERROR CAUSED BY TEMPERATURE VARIATION 85
3.3.1 Bias Variation by Temperature 86
3.3.2 Scale factor Variation by Temperature 87
CHAPTER 4. A SOLUTION FOR GPS FAILURE USING MAGNETOMETER 91
4.1 GPS/INS AND MAGNETOMETER INTEGRATED NAVIGATION SYSTEM 91
4.1.1 Magnetic Heading Integration Method 91
4.1.2 Magnetic Vector Integration Method 93
4.2 OBSERVABILITY ANALYSIS OF GPS/INS INTEGRATED NAVIGATION SYSTEM 96
4.2.1 Observability Analysis of GPS measurement 97
4.2.2 Observability Analysis of Magnetic Vector Measurement 114
4.3 SIMULATION RESULTS 118
4.3.1 Simulation Setup 118
4.3.2 Simulation results in case of GPS is available 122
4.3.3 Simulation Results in Case of GPS is Not Available 128
4.4 EXPERIMENT RESULTS 133
4.4.1 Experiment Setup 133
4.4.2 Performance Comparison According to Calibration Method 138
4.4.3 Performance Comparison According to Integration Method 141
CHAPTER 5. A SOLUTION FOR IMU FAILURE USING MAGNETOMETER 149
5.1 SINGLE-ANTENNA GPS BASED ATTITUDE DETERMINATION 149
5.1.1 Principles of Attitude Determination 150
5.1.2 Performance and Limitation 151
5.2 ATTITUDE ESTIMATION METHOD BY INTEGRATING SINGLE-ANTENNA GPS ATTITUDE WITH MULTI-SENSOR FOR IMU FAILURE 152
5.2.1 Attitude Estimation Method for Total IMU Failure 153
5.2.2 Attitude Estimation Method for Gyroscope Failure 155
5.2.3 Attitude Estimation Method for Accelerometer Failure 158
5.3 SIMULATION RESULTS 161
5.3.1 Simulation for Steady Wind 161
5.3.2 Simulation for Unsteady Wind 163
5.4 EXPERIMENT RESULTS 166
CHAPTER 6. CONCLUSION AND FUTURE WORK 169
BIBLIOGRAPHY 171
ABSTRACT IN KOREAN 179
-
dc.formatapplication/pdf-
dc.format.extent9405163 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subjectMagnetometer-
dc.subjectGPS/INS-
dc.subjectSensor Failure-
dc.subjectNavigation-
dc.subjectAttitude-
dc.subjectUAV-
dc.subject.ddc621-
dc.titleSensor Failure Scenarios and Corresponding Solutions of Three Axis Magnetometer Integrated GPS/INS UAV Navigation System-
dc.title.alternative3축 지자기 센서 결합 GPS/INS 무인기 항법 시스템의 센서 고장 시나리오 및 대처 방안-
dc.typeThesis-
dc.contributor.AlternativeAuthor노희권-
dc.description.degreeDoctor-
dc.citation.pagesxvi, 180-
dc.contributor.affiliation공과대학 기계항공공학부-
dc.date.awarded2017-02-
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Mechanical Aerospace Engineering (기계항공공학부)Theses (Ph.D. / Sc.D._기계항공공학부)
Files in This Item:
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse