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第1章 绪论 1

参考文献 7

第2章 惯性、卫星和天文导航系统工作原理 9

2.1引言 9

2.2导航中常用的坐标系及地球参考模型 9

2.2.1导航中常用的坐标系 9

2.2.2坐标系的转换 11

2.2.3地球参考模型 14

2.3惯性导航系统 18

2.3.1惯性导航系统工作原理 18

2.3.2捷联惯性导航系统误差方程与误差传播特性 21

2.4卫星导航系统 28

2.4.1卫星导航系统工作原理 28

2.4.2卫星导航系统误差特性分析 30

2.5天文导航系统 32

2.5.1自主天文定位原理 33

2.5.2天文定姿原理 40

2.5.3天文导航系统中的恒星敏感器及其误差特性分析 42

Chapter 1 Introduction 1

References 7

Chapter 2 Working Principles of INS,GNSS and CNS 9

2.1 Introduction 9

2.2 Coordinates Systems and The Earth Model in Navigation 9

2.2.1 Coordinates Systems in Navigation 9

2.2.2 Coordinates Frame Transformation 11

2.2.3 Earth Model 14

2.3 Inertial Navigation System 18

2.3.1 Working Principles of INS 18

2.3.2 Error Models and Error Propagation Characteristics of INS 21

2.4 Global Navigation Satellite System 28

2.4.1 Working Principles of GNSS 28

2.4.2 Error Analysis of GNSS 30

2.5 Celestial Navigation System 32

2.5.1 Principles of Positioning 33

2.5.2 Principles of Attitude Determination 40

2.5.3 Star Sensors in Celestial Navigation System and Its Error Characteristics 42

参考文献 46

第3章 导航系统的先进滤波方法 49

3.1引言 49

3.2卡尔曼滤波 50

3.3扩展卡尔曼滤波 52

3.4 Unscented卡尔曼滤波 56

3.5粒子滤波 58

3.6 Unscented粒子滤波 60

3.7预测滤波 61

3.8联邦滤波 64

参考文献 66

第4章 捷联惯性导航系统建模标定方法及高动态捷联算法 69

4.1引言 69

4.2陀螺仪误差建模、测试与补偿 70

4.2.1陀螺仪误差模型 70

4.2.2陀螺仪标度因数与输入轴失准角的解耦测试方法 72

4.2.3陀螺仪标度因数误差分析及分段插值补偿方法 76

4.2.4硅MEMS陀螺仪温度误差建模 80

4.3捷联惯性测量单元的标定方法 82

4.3.1动静结合的混合标定方法 83

4.3.2低精度MIMU六位置正反转标定方法 90

References 46

Chapter3 Filters in Navigation System 49

3.1 Introduction 49

3.2 Kalman Filter 60

3.3 Extended Kalman Filter 52

3.4 Unscented Kalman Filter 56

3.5 Particle Filter 58

3.6 Unscented Partical Filter 60

3.7 Predictive Filter 61

3.8 Federal Filter 64

References 66

Chapter 4 Modeling and Calibration of INS and The High Dynamic Strapdown Inertial Algorithm 69

4.1 Introduction 69

4.2 Error Modeling, Testing and Compensation of Inertial Sensors 70

4.2.1 Error Models of Gyroscopes 70

4.2.2 Test Method of Decupling GycoScale Factors and Input Axis Misalignment Angle 72

4.2.3 Error Analysis of Gyroscope Scale Factors and Its Piecewise Interpolation Compensatory Method 76

4.2.4 Temperature Error Modeling of Silicon Mems Gyroscope 80

4.3 Inertaial Measurements Units Calibration 82

4.3.1 Calibration Combing Dynamic and Static Methods 83

4.3.2 Reversible Six Positions Calibration Method for Low Accuracy MIMU 90

4.3.3基于神经网络的MIMU标度因数误差补偿方法 94

4.4高动态捷联惯性导航系统算法 102

4.4.1圆锥运动分析及圆锥误差补偿算法评价准则 103

4.4.2一种改进的单子样的旋转矢量姿态算法 104

参考文献 112

第5章 惯性/卫星组合导航方法 116

5.1引言 116

5.2惯性/卫星组合导航原理 117

5.2.1惯性/卫星组合导航组合模式 117

5.2.2惯性/卫星组合导航基本原理 118

5.3惯性/卫星组合导航系统的建模方法 120

5.3.1基于φ角的惯性/卫星组合导航系统线性建模方法 120

5.3.2基于四元数误差的惯性/卫星组合导航系统非线性建模方法 123

5.4高精度惯性/卫星组合导航方法 129

5.4.1基于混合校正的惯性/卫星组合导航方法 130

5.4.2基于可观测度归一化处理方法的自适应反馈校正滤波方法 133

4.3.3 Error Compensation Method for Scale Factor of MIMU Based on Neural Network 94

4.4 High Dynamic Strapdown Inertial Algorithm 102

4.4.1 The Analysis of Cone Motion and Evaluation Criterion of Cone Compensation Algorithm 103

4.4.2 A New Attitude Determinationro Algorithm Using Improved Single-Subsample Rolling Vector 104

References 112

Chapter 5 INS/GNSS Integrated Navigation Method 116

5.1 Introduction 116

5.2 Principles of INS/GNSS Integrated Navigation 117

5.2.1 Integrated Modes of INS/CNS Integrated Navigation 117

5.2.2 Principles of INS/GNSS Integrated Navigation 118

5.3 Modeling of INS/GNSS Integrated Navigation 120

5.3.1 Linear Modeling Method Based onφAngle 120

5.3.2 Nonlinear Modeling Method Based on Quaternion Error 123

5.4 High Accuracy INS/GNSS Integrated Navigation Method 129

5.4.1 SINS/GNSS Integrated Navigation Method Based on Mixed Correction 130

5.4.2 Adaptive Feed-Back Filter Based on Observability Normalization 133

5.4.3基于卡尔曼滤波新息正交性的惯性/卫星抗野值组合导航方法 137

5.4.4基于可观测度分析与杆臂误差补偿的空中机动对准方法 140

5.5微小型、低成本惯性/卫星组合导航方法 144

5.5.1基于UKF的微小型、低成本惯性/卫星组合导航方法 145

5.5.2大失准角下惯性/卫星组合导航系统的空中机动对准方法 146

5.5.3基于微惯性测量单元/磁强计的组合导航方法 150

5.6机载SAR成像运动补偿用惯性/卫星组合导航系统 161

5.6.1机载SAR成像运动补偿用惯性/卫星组合导航系统原理 161

5.6.2机载惯性/卫星组合导航系统设计与实现 162

5.6.3机载SAR成像运动补偿用惯性/卫星组合导航系统试验 166

参考文献 172

第6章 惯性/天文组合导航方法 176

6.1引言 176

6.2惯性/天文组合导航基本原理 177

5.4.3 SINS/GNSS Integrated Navigation Method Based on Kalman Filtering Orthogonality of Innovation for Restraining Outliers 137

5.4.4 A New In-flight Alignment Method Based on Observability Analysis and Level-arm Error Compensation 140

5.5 Micro-low Cost INS/GNSS Integrated Navigation Method 144

5.5.1 Low Cost INS/GNSS Integrated Navigation Method Based on UKF 145

5.5.2 The In-flight Alignment Method of INS/GNSS Integrated Navigation System in Big Misalignment Angle 146

5.5.3 The Integrated Navigation Method Based on IMU/Magnetometer 150

5.6 INS/GNSS Integrated Navigation System in Motion Compensation System for Airborne SAR Imaging 161

5.6.1 Principle of INS/GNSS Integrated Navigation System 161

5.6.2 INS/GNSS Integrated Navigation System Design and Implementation 162

5.6.3 INS/GNSS Integrated Navigation Experiments 166

References 172

Chapter 6 INS/CNS Integrated Navigation Method 176

6.1 Introduction 176

6.2 Principles of INS/CNS Integrated Navigation 177

6.2.1惯性/天文组合导航系统的工作模式 177

6.2.2惯性/天文组合导航系统的组合方式 179

6.2.3基于天文量测信息的惯性器件误差修正原理 180

6.3惯性/天文组合导航系统建模方法 181

6.3.1惯性/天文组合导航系统状态方程 181

6.3.2惯性/天文组合导航系统量测方程 183

6.4弹道导弹惯性/天文组合导航新方法 184

6.4.1基于天文量测信息的导弹发射点初始位置误差校正原理 184

6.4.2基于UKF的弹道导弹惯性/天文组合导航方法 185

6.5月球车的惯性/天文组合导航方法 189

6.5.1月球车的捷联惯性导航方法 190

6.5.2一种基于UPF的月球车惯性/天文组合导航方法 190

6.6卫星的惯性/天文组合定姿方法 195

6.6.1卫星定姿系统方程 195

6.6.2一种基于EKF的分段信息融合的惯性/天文组合定姿方法 197

6.2.1 Working Modes of INS/CNS Integrated Navigation System 177

6.2.2 Integrated Modes of INS/CNS Integrated Navigation System 179

6.2.3 Correction of Inertial Sensor Errors Employing Celestial Information 180

6.3 Modeling of INS/CNS Integrated Navigation System 181

6.3.1 State Equations 181

6.3.2 Measurement Equations 183

6.4 New INS/CNS Integrated Method for Missile 184

6.4.1 Correction of The Emission Point Position Error Based on The Celestial Information 184

6.4.2 INS/ CNS Integrated Navigation Method Based on UKF 185

6.5 INS/CNS Integrated Navigation Method for Lunar Rover 189

6.5.1 Strapdown Inertial Navigation Method for Lunar Rover 190

6.5.2 SINS/CNS Integrated Navigation Method for Lunar Rover Based on UPF 190

6.6 INS/CNS Integrated Attitude Determination Method for Satellites 195

6.6.1 System Equations of Attitude Determination System for Spacecrafts 195

6.6.2 SINS/CNS Integrated Attitude Determination Method Based on EKF and Sectional Information Fusion 197

6.6.3基于UKF的卫星最小参数姿态矩阵估计方法 201

6.6.4一种基于QUEST+UKF+最优REQUEST的自适应分段信息融合定姿方法 206

参考文献 212

第7章 惯性/天文/卫星组合导航方法 215

7.1引言 215

7.2惯性/天文/卫星组合导航原理 216

7.2.1惯性/天文/卫星组合导航基本原理 216

7.2.2惯性/天文/卫星组合导航的组合模式 216

7.2.3惯性/天文/卫星组合导航系统的建模 221

7.3基于联邦UKF的惯性/天文/卫星组合导航方法 222

7.4基于优化信息分配因子的联邦滤波惯性/天文/卫星组合导航方法 225

7.4.1联邦滤波方程及信息分配过程 226

7.4.2基于信息分配因子优化的联邦滤波惯性/天文/卫星组合导航方法 227

7.4.3基于遗传算法优化信息分配因子的联邦滤波惯性/天文/卫星组合导航方法 228

6.6.3 Estimation Method for Satellite Minimal Parameter Attitude Matrix Based on UKF 201

6.6.4 An Adaptive Segmented Information Fusion Attitude Determination Method Based on QUEST+UKF+Optimal Request 206

References 212

Chapter 7 INS/CNS/GNSS Integrated Navigation Method 215

7.1 Introduction 215

7.2 Principles of INS/CNS/GNSS Integrated Navigation 216

7.2.1 Basic Principles of INS/CNS/GNSS Integrated Navigation 216

7.2.2 Integrated Modes of INS/CNS/GNSS Integrated Navigation System 216

7.2.3 System Modeling of INS/CNS/GNSS Integrated Navigation System 221

7.3 INS/CNS/GNSS Integrated Navigation Method Based on Federal UKF Filter 222

7.4 INS/CNS/GNSS Integrated Navigation Method Based on Federal Filter With Optimal Information Distribution factor 225

7.4.1 Federal Filter Equations and Process of Information Distribution 226

7.4.2 The SINS/CNS/GNSS Integrated Navigation Federal Filter Method Based on The Optimized Information Distribution Factor 227

7.4.3 The SINS/CNS/GNSS Integrated Navigation Federal Filter Method Based on The Information Distribution Factor Optimized by Genetical Algorithm 228

7.5一种基于衰减因子卡尔曼滤波的惯性/天文/卫星组合导航方法 234

7.5.1状态方程与量测方程 234

7.5.2一种新的衰减因子自适应滤波器 235

7.5.3基于新的衰减因子自适应滤波的惯性/天文/卫星组合导航方法 238

7.6基于多模型自适应滤波的惯性/天文/卫星组合导航方法 240

7.6.1基于递归型交互式多模型自适应滤波的惯性/天文/卫星的组合导航方法 241

7.6.2基于遗传多模型自适应滤波的惯性/天文/卫星组合导航方法 246

参考文献 250

第8章 惯性/天文/卫星组合导航方法的实时性研究 252

8.1引言 252

8.2分段线性定常系统可观测性分析理论与方法 253

8.2.1分段线性定常系统可观测性分析理论 253

8.2.2一种改进的基于奇异值分解的系统状态可观测度分析方法 257

8.3基于改进可观测度分析的惯性/天文组合导航系统降维滤波器设计 259

8.4基于改进可观测度分析的惯性/卫星组合导航系统降维滤波器设计 263

7.5 INS/CNS/GNSS Integrated Navigation Methods Based on Fading Factor 234

7.5.1 State Equations and Measurement Equations 234

7.5.2 A New Adaptive Filter Based on Fading Factor 235

7.5.3 SINS/CNS/GNSS Integrated Navigation Based on New Adaptive Filter 238

7.6 The SINS/CNS/GNSS Integrated Navigaon Based on Multimode Adaptive Kalman Filter 240

7.6.1 The SINS/ CNS/GNSS Integrated Navigation Based on Recursive Interactive Multimode Adaptive Kalman Filter 241

7.6.2 The SINS/CNS/GNSS Integrated Navigation Based on Genetic Algorithm Multimode Adaptive Kalman Filter 246

References 250

Chapter 8 Study on Real-time Ability of INS/CNS/GNSS Integrated Navigation Method 252

8.1 Introduction 252

8.2 Observability Analysis Method 253

8.2.1 The Princile of PWCS Observability Analysis 253

8.2.2 An Observability Analysis Based on Improved Singular Value Decomposition 257

8.3 The Design of Dimensionality Reduction Filter Based on Improved Observability Analysis for SINS/CNS Integrated Navigation 259

8.4 The Design of Dimensionality Reduction Filter Based on Improved Observability Analysis for SINS/GNSS Integrated Navigation 263

8.5基于降维滤波的惯性/天文/卫星组合导航系统联邦滤波器设计 267

8.6一种惯性/天文/卫星组合导航算法的优化方法 271

参考文献 275

第9章 惯性/天文/卫星组合导航半物理仿真系统 277

9.1引言 277

9.2惯性/天文/卫星组合导航半物理仿真系统原理与组成 278

9.2.1惯性/天文/卫星组合导航半物理仿真系统原理 278

9.2.2惯性/天文/卫星组合导航半物理仿真系统组成 280

9.3惯性/天文/卫星组合导航半物理仿真系统的实现与试验 294

9.3.1惯性/天文/卫星组合导航半物理仿真系统的实现 295

9.3.2惯性/天文/卫星组合导航半物理仿真系统的试验 303

参考文献 305

第10章 惯性/天文/卫星组合导航技术展望 307

10.1组合导航技术的发展与展望 307

10.1.1惯性/天文/卫星组合导航系统的精确建模技术 307

10.1.2惯性/天文/卫星组合导航系统的信息融合与先进滤波方法 308

8.5 The Design of Federal Filter Based on Dimensionality Reduction Filter for SINS/CNS/GNSS Integrated Navigation 267

8.6 An Optimal Method for SINS/CNS/GNSS Integrated Navigation 271

References 275

Chapter 9 Semi-physical Simulation Technology of INS/CNS/GNSS Integrated Navigation 277

9.1 Introduction 277

9.2 Principles of Hybrid Simulation of INS/CNS/GNSS Integrated Navigation 278

9.2.1 Principles of Semi-physical Simulation of INS/CNS/GNSS Integrated Navigation 278

9.2.2 Compositions of INS/CNS/GNSS Integrated Navigation System 280

9.3 Implementations and Experiments of Semi-physical INS/CNS/GNSS Integrated Navigation System 294

9.3.1 Implementations of Semi-physical INS/CNS/GNSS Integrated Navigation System 295

9.3.2 Experiments of Semi-physical INS/CNS/GNSS Integrated Navigation System 303

References 305

Chapter 10 Prospect of INS/CNS/GNSS Integrated Navigation Technology 307

10.1 Development and Prospect of INS/ CNS/GNSS Integrated Navigation 307

10.1.1 Accurate Modeling of INS/ CNS/GNSS Integrated Navigation System 307

10.1.2 Information Fusion and Advanced Filters in INS/CNS/GNSS Integrated Navigation System 308

10.1.3基于先进控制理论的惯性/天文/卫星组合导航方法 309

10.1.4基于集成一体化的惯性/天文/卫星组合导航系统技术 312

10.1.5惯性/天文/卫星组合导航技术的应用 312

10.2结束语 313

参考文献 314

10.1.3 Advanced Control Theories in INS/CNS/GNSS Integrated Navigation System 309

10.1.4 INS/CNS/GNSS Integrated Navigation System Technology Based on Integration Technology 312

10.1.5 Applications of INS/CNS/GNSS Integrated Navigation Technology 312

10.2Summary 313

References 314