Principles of GNSS, inertial, and multisensor integrated navigation systems / Paul D. Groves.
This newly revised and greatly expanded edition of the popular Artech House book Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems offers you a current and comprehensive understanding of satellite navigation, inertial navigation, terrestrial radio navigation, dead reckoning...
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| Online Access: |
Full Text (via ProQuest) |
|---|---|
| Main Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boston :
Artech House,
[2013]
|
| Edition: | Second edition. |
| Series: | GNSS technology and applications series.
|
| Subjects: |
Table of Contents:
- Machine generated contents note: ch. 1 Introduction
- 1.1. Fundamental Concepts
- 1.2. Dead Reckoning
- 1.3. Position Fixing
- 1.3.1. Position-Fixing Methods
- 1.3.2. Signal-Based Positioning
- 1.3.3. Environmental Feature Matching
- 1.4. The Navigation System
- 1.4.1. Requirements
- 1.4.2. Context
- 1.4.3. Integration
- 1.4.4. Aiding
- 1.4.5. Assistance and Cooperation
- 1.4.6. Fault Detection
- 1.5. Overview of the Book
- References
- ch. 2 Coordinate Frames, Kinematics, and the Earth
- 2.1. Coordinate Frames
- 2.1.1. Earth-Centered Inertial Frame
- 2.1.2. Earth-Centered Earth-Fixed Frame
- 2.1.3. Local Navigation Frame
- 2.1.4. Local Tangent-Plane Frame
- 2.1.5. Body Frame
- 2.1.6. Other Frames
- 2.2. Attitude, Rotation, and Resolving Axes Transformations
- 2.2.1. Euler Attitude
- 2.2.2. Coordinate Transformation Matrix
- 2.2.3. Quaternion Attitude
- 2.2.4. Rotation Vector
- 2.3. Kinematics
- 2.3.1. Angular Rate
- 2.3.2. Cartesian Position
- 2.3.3. Velocity
- 2.3.4. Acceleration
- 2.3.5. Motion with Respect to a Rotating Reference Frame
- 2.4. Earth Surface and Gravity Models
- 2.4.1. The Ellipsoid Model of the Earth's Surface
- 2.4.2. Curvilinear Position
- 2.4.3. Position Conversion
- 2.4.4. The Geoid, Orthometric Height, and Earth Tides
- 2.4.5. Projected Coordinates
- 2.4.6. Earth Rotation
- 2.4.7. Specific Force, Gravitation, and Gravity
- 2.5. Frame Transformations
- 2.5.1. Inertial and Earth Frames
- 2.5.2. Earth and Local Navigation Frames
- 2.5.3. Inertial and Local Navigation Frames
- 2.5.4. Earth and Local Tangent-Plane Frames
- 2.5.5. Transposition of Navigation Solutions
- References
- ch. 3 Kalman Filter-Based Estimation
- 3.1. Introduction
- 3.1.1. Elements of the Kalman Filter
- 3.1.2. Steps of the Kalman Filter
- 3.1.3. Kalman Filter Applications
- 3.2. Algorithms and Models
- 3.2.1. Definitions
- 3.2.2. Kalman Filter Algorithm
- 3.2.3. System Model
- 3.2.4. Measurement Model
- 3.2.5. Kalman Filter Behavior and State Observability
- 3.2.6. Closed-Loop Kalman Filter
- 3.2.7. Sequential Measurement Update
- 3.3. Implementation Issues
- 3.3.1. Tuning and Stability
- 3.3.2. Algorithm Design
- 3.3.3. Numerical Issues
- 3.3.4. Time Synchronization
- 3.3.5. Kalman Filter Design Process
- 3.4. Extensions to the Kalman Filter
- 3.4.1. Extended and Linearized Kalman Filter
- 3.4.2. Unscented Kalman Filter
- 3.4.3. Time-Correlated Noise
- 3.4.4. Adaptive Kalman Filter
- 3.4.5. Multiple-Hypothesis Filtering
- 3.4.6. Kalman Smoothing
- 3.5. The Particle Filter
- References
- ch. 4 Inertial Sensors
- 4.1. Accelerometers
- 4.1.1. Pendulous Accelerometers
- 4.1.2. Vibrating-Beam Accelerometers
- 4.2. Gyroscopes
- 4.2.1. Optical Gyroscopes
- 4.2.2. Vibratory Gyroscopes
- 4.3. Inertial Measurement Units
- 4.4. Error Characteristics
- 4.4.1. Biases
- 4.4.2. Scale Factor and Cross-Coupling Errors
- 4.4.3. Random Noise
- 4.4.4. Further Error Sources
- 4.4.5. Vibration-Induced Errors
- 4.4.6. Error Models
- References
- ch. 5 Inertial Navigation
- 5.1. Introduction to Inertial Navigation
- 5.2. Inertial-Frame Navigation Equations
- 5.2.1. Attitude Update
- 5.2.2. Specific-Force Frame Transformation
- 5.2.3. Velocity Update
- 5.2.4. Position Update
- 5.3. Earth-Frame Navigation Equations
- 5.3.1. Attitude Update
- 5.3.2. Specific-Force Frame Transformation
- 5.3.3. Velocity Update
- 5.3.4. Position Update
- 5.4. Local-Navigation-Frame Navigation Equations
- 5.4.1. Attitude Update
- 5.4.2. Specific-Force Frame Transformation
- 5.4.3. Velocity Update
- 5.4.4. Position Update
- 5.4.5. Wander-Azimuth Implementation
- 5.5. Navigation Equations Optimization
- 5.5.1. Precision Attitude Update
- 5.5.2. Precision Specific-Force Frame Transformation
- 5.5.3. Precision Velocity and Position Updates
- 5.5.4. Effects of Sensor Sampling Interval and Vibration
- 5.5.5. Design Tradeoffs
- 5.6. Initialization and Alignment
- 5.6.1. Position and Velocity Initialization
- 5.6.2. Attitude Initialization
- 5.6.3. Fine Alignment
- 5.7. INS Error Propagation
- 5.7.1. Short-Term Straight-Line Error Propagation
- 5.7.2. Medium- and Long-Term Error Propagation
- 5.7.3. Maneuver-Dependent Errors
- 5.8. Indexed IMU
- 5.9. Partial IMU
- References
- ch. 6 Dead Reckoning, Attitude, and Height Measurement
- 6.1. Attitude Measurement
- 6.1.1. Magnetic Heading
- 6.1.2. Marine Gyrocompass
- 6.1.3. Strapdown Yaw-Axis Gyro
- 6.1.4. Heading from Trajectory
- 6.1.5. Integrated Heading Determination
- 6.1.6. Accelerometer Leveling and Tilt Sensors
- 6.1.7. Horizon Sensing
- 6.1.8. Attitude and Heading Reference System
- 6.2. Height and Depth Measurement
- 6.2.1. Barometric Altimeter
- 6.2.2. Depth Pressure Sensor
- 6.2.3. Radar Altimeter
- 6.3. Odometry
- 6.3.1. Linear Odometry
- 6.3.2. Differential Odometry
- 6.3.3. Integrated Odometry and Partial IMU
- 6.4. Pedestrian Dead Reckoning Using Step Detection
- 6.5. Doppler Radar and Sonar
- 6.6. Other Dead-Reckoning Techniques
- 6.6.1. Correlation-Based Velocity Measurement
- 6.6.2. Air Data
- 6.6.3. Ship's Speed Log
- References
- ch. 7 Principles of Radio Positioning
- 7.1. Radio Positioning Configurations and Methods
- 7.1.1. Self-Positioning and Remote Positioning
- 7.1.2. Relative Positioning
- 7.1.3. Proximity
- 7.1.4. Ranging
- 7.1.5. Angular Positioning
- 7.1.6. Pattern Matching
- 7.1.7. Doppler Positioning
- 7.2. Positioning Signals
- 7.2.1. Modulation Types
- 7.2.2. Radio Spectrum
- 7.3. User Equipment
- 7.3.1. Architecture
- 7.3.2. Signal Timing Measurement
- 7.3.3. Position Determination from Ranging
- 7.4. Propagation, Error Sources, and Positioning Accuracy
- 7.4.1. Ionosphere, Troposphere, and Surface Propagation Effects
- 7.4.2. Attenuation, Reflection, Multipath, and Diffraction
- 7.4.3. Resolution, Noise, and Tracking Errors
- 7.4.4. Transmitter Location and Timing Errors
- 7.4.5. Effect of Signal Geometry
- References
- ch. 8 GNSS: Fundamentals, Signals, and Satellites
- 8.1. Fundamentals of Satellite Navigation
- 8.1.1. GNSS Architecture
- 8.1.2. Signals and Range Measurement
- 8.1.3. Positioning
- 8.1.4. Error Sources and Performance Limitations
- 8.2. The Systems
- 8.2.1. Global Positioning System
- 8.2.2. GLONASS
- 8.2.3. Galileo
- 8.2.4. Beidou
- 8.2.5. Regional Systems
- 8.2.6. Augmentation Systems
- 8.2.7. System Compatibility
- 8.3. GNSS Signals
- 8.3.1. Signal Types
- 8.3.2. Global Positioning System
- 8.3.3. GLONASS
- 8.3.4. Galileo
- 8.3.5. Beidou
- 8.3.6. Regional Systems
- 8.3.7. Augmentation Systems
- 8.4. Navigation Data Messages
- 8.4.1. GPS
- 8.4.2. GLONASS
- 8.4.3. Galileo
- 8.4.4. SBAS
- 8.4.5. Time Base Synchronization
- 8.5. Satellite Orbits and Geometry
- 8.5.1. Satellite Orbits
- 8.5.2. Satellite Position and Velocity
- 8.5.3. Range, Range Rate, and Line of Sight
- 8.5.4. Elevation and Azimuth
- References
- ch. 9 GNSS: User Equipment Processing and Errors
- 9.1. Receiver Hardware and Antenna
- 9.1.1. Antennas
- 9.1.2. Reference Oscillator
- 9.1.3. Receiver Front End
- 9.1.4. Baseband Signal Processor
- 9.2. Ranging Processor
- 9.2.1. Acquisition
- 9.2.2. Code Tracking
- 9.2.3. Carrier Tracking
- 9.2.4. Tracking Lock Detection
- 9.2.5. Navigation-Message Demodulation
- 9.2.6. Carrier-Power-to-Noise-Density Measurement
- 9.2.7. Pseudo-Range, Pseudo-Range-Rate, and Carrier-Phase Measurements
- 9.3. Range Error Sources
- 9.3.1. Ephemeris Prediction and Satellite Clock Errors
- 9.3.2. Ionosphere and Troposphere Propagation Errors
- 9.3.3. Tracking Errors
- 9.3.4. Multipath, Nonline-of-Sight, and Diffraction
- 9.4. Navigation Processor
- 9.4.1. Single-Epoch Navigation Solution
- 9.4.2. Filtered Navigation Solution
- 9.4.3. Signal Geometry and Navigation Solution Accuracy
- 9.4.4. Position Error Budget
- References
- ch.
- 10 GNSS: Advanced Techniques
- 10.1. Differential GNSS
- 10.1.1. Spatial and Temporal Correlation of GNSS Errors
- 10.1.2. Local and Regional Area DGNSS
- 10.1.3. Wide Area DGNSS and Precise Point Positioning
- 10.1.4. Relative GNSS
- 10.2. Real-Time Kinematic Carrier-Phase Positioning and Attitude Determination
- 10.2.1. Principles of Accumulated Delta Range Positioning
- 10.2.2. Single-Epoch Navigation Solution Using Double-Differenced ADR
- 10.2.3. Geometry-Based Integer Ambiguity Resolution
- 10.2.4. Multifrequency Integer Ambiguity Resolution
- 10.2.5. GNSS Attitude Determination
- 10.3. Interference Rejection and Weak Signal Processing
- 10.3.1. Sources of Interference, Jamming, and Attenuation
- 10.3.2. Antenna Systems
- 10.3.3. Receiver Front-End Filtering
- 10.3.4. Extended Range Tracking
- 10.3.5. Receiver Sensitivity
- 10.3.6.Combined Acquisition and Tracking
- 10.3.7. Vector Tracking
- 10.4. Mitigation of Multipath Interference and Nonline-of-Sight Reception
- 10.4.1. Antenna-Based Techniques
- 10.4.2. Receiver-Based Techniques
- 10.4.3. Navigation-Processor-Based Techniques
- 10.5. Aiding, Assistance, and Orbit Prediction
- 10.5.1. Acquisition and Velocity Aiding
- 10.5.2. Assisted GNSS
- 10.5.3. Orbit Prediction
- 10.6. Shadow Matching
- References
- ch. 11 Long- and Medium-Range Radio Navigation
- 11.1. Aircraft Navigation Systems
- 11.1.1. Distance Measuring Equipment
- 11.1.2. Range-Bearing Systems
- 11.1.3. Nondirectional Beacons
- 11.1.4. JTIDS/MIDS Relative Navigation
- 11.1.5. Future Air Navigation Systems
- 11.2. Enhanced Loran
- 11.2.1. Signals
- 11.2.2. User Equipment and Positioning
- 11.2.3. Error Sources
- 11.2.4. Differential Loran
- 11.3. Phone Positioning
- 11.3.1. Proximity and Pattern Matching
- 11.3.2. Ranging
- 11.4. Other Systems
- 11.4.1. Iridium Positioning
- 11.4.2. Marine Radio Beacons
- 11.4.3. AM Radio Broadcasts
- 11.4.4. FM Radio Broadcasts
- 11.4.5. Digital Television and Radio
- 11.4.6. Generic Radio Positioning
- References
- ch. 12 Short-Range Positioning
- 12.1. Pseudolites
- 12.1.1. In-Band Pseudolites
- 12.1.2. Locata and Terralite XPS
- 12.1.3. Indoor Messaging System
- 12.2. Ultrawideband
- 12.2.1. Modulation Schemes
- 12.2.2. Signal Timing
- 12.2.3. Positioning.
- Note continued: 12.3. Short-Range Communications Systems
- 12.3.1. Wireless Local Area Networks (Wi-Fi)
- 12.3.2. Wireless Personal Area Networks
- 12.3.3. Radio Frequency Identification
- 12.3.4. Bluetooth Low Energy
- 12.3.5. Dedicated Short-Range Communication
- 12.4. Underwater Acoustic Positioning
- 12.5. Other Positioning Technologies
- 12.5.1. Radio
- 12.5.2. Ultrasound
- 12.5.3. Infrared
- 12.5.4. Optical
- 12.5.5. Magnetic
- References
- ch. 13 Environmental Feature Matching
- 13.1. Map Matching
- 13.1.1. Digital Road Maps
- 13.1.2. Road Link Identification
- 13.1.3. Road Positioning
- 13.1.4. Rail Map Matching
- 13.1.5. Pedestrian Map Matching
- 13.2. Terrain-Referenced Navigation
- 13.2.1. Sequential Processing
- 13.2.2. Batch Processing
- 13.2.3. Performance
- 13.2.4. Laser TRN
- 13.2.5. Sonar TRN
- 13.2.6. Barometric TRN
- 13.2.7. Terrain Database Height Aiding
- 13.3. Image-Based Navigation
- 13.3.1. Imaging Sensors
- 13.3.2. Image Feature Comparison
- 13.3.3. Position Fixing Using Individual Features
- 13.3.4. Position Fixing by Whole-Image Matching
- 13.3.5. Visual Odometry
- 13.3.6. Feature Tracking
- 13.3.7. Stellar Navigation
- 13.4. Other Feature-Matching Techniques
- 13.4.1. Gravity Gradiometry
- 13.4.2. Magnetic Field Variation
- 13.4.3. Celestial X-Ray Sources
- References
- ch. 14 INS/GNSS Integration
- 14.1. Integration Architectures
- 14.1.1. Correction of the Inertial Navigation Solution
- 14.1.2. Loosely Coupled Integration
- 14.1.3. Tightly Coupled Integration
- 14.1.4. GNSS Aiding
- 14.1.5. Deeply Coupled Integration
- 14.2. System Model and State Selection
- 14.2.1. State Selection and Observability
- 14.2.2. INS State Propagation in an Inertial Frame
- 14.2.3. INS State Propagation in an Earth Frame
- 14.2.4. INS State Propagation Resolved in a Local Navigation Frame
- 14.2.5. Additional IMU Error States
- 14.2.6. INS System Noise
- 14.2.7. GNSS State Propagation and System Noise
- 14.2.8. State Initialization
- 14.3. Measurement Models
- 14.3.1. Loosely Coupled Integration
- 14.3.2. Tightly Coupled Integration
- 14.3.3. Deeply Coupled Integration
- 14.3.4. Estimation of Attitude and Instrument Errors
- 14.4. Advanced INS/GNSS Integration
- 14.4.1. Differential GNSS
- 14.4.2. Carrier-Phase Positioning
- 14.4.3. GNSS Attitude
- 14.4.4. Large Heading Errors
- 14.4.5. Advanced IMU Error Modeling
- 14.4.6. Smoothing
- References
- ch. 15 INS Alignment, Zero Updates, and Motion Constraints
- 15.1. Transfer Alignment
- 15.1.1. Conventional Measurement Matching
- 15.1.2. Rapid Transfer Alignment
- 15.1.3. Reference Navigation System
- 15.2. Quasi-Stationary Alignment
- 15.2.1. Coarse Alignment
- 15.2.2. Fine Alignment
- 15.3. Zero Updates
- 15.3.1. Stationary-Condition Detection
- 15.3.2. Zero Velocity Update
- 15.3.3. Zero Angular Rate Update
- 15.4. Motion Constraints
- 15.4.1. Land Vehicle Constraints
- 15.4.2. Pedestrian Constraints
- 15.4.3. Ship and Boat Constraint
- References
- ch. 16 Multisensor Integrated Navigation
- 16.1. Integration Architectures
- 16.1.1. Cascaded Single-Epoch Integration
- 16.1.2. Centralized Single-Epoch Integration
- 16.1.3. Cascaded Filtered Integration
- 16.1.4. Centralized Filtered Integration
- 16.1.5. Federated Filtered Integration
- 16.1.6. Hybrid Integration Architectures
- 16.1.7. Total-State Kalman Filter Employing Prediction
- 16.1.8. Error-State Kalman Filter
- 16.1.9. Primary and Reversionary Moding
- 16.1.10. Context-Adaptive Moding
- 16.2. Dead Reckoning, Attitude, and Height Measurement
- 16.2.1. Attitude
- 16.2.2. Height and Depth
- 16.2.3. Odometry
- 16.2.4. Pedestrian Dead Reckoning Using Step Detection
- 16.2.5. Doppler Radar and Sonar
- 16.2.6. Visual Odometry and Terrain-Referenced Dead Reckoning
- 16.3. Position-Fixing Measurements
- 16.3.1. Position Measurement Integration
- 16.3.2. Ranging Measurement Integration
- 16.3.3. Angular Measurement Integration
- 16.3.4. Line Fix Integration
- 16.3.5. Handling Ambiguous Measurements
- 16.3.6. Feature Tracking and Mapping
- 16.3.7. Aiding of Position-Fixing Systems
- References
- ch. 17 Fault Detection, Integrity Monitoring, and Testing
- 17.1. Failure Modes
- 17.1.1. Inertial Navigation
- 17.1.2. Dead Reckoning, Attitude, and Height Measurement
- 17.1.3. GNSS
- 17.1.4. Terrestrial Radio Navigation
- 17.1.5. Environmental Feature Matching and Tracking
- 17.1.6. Integration Algorithm
- 17.1.7. Context
- 17.2. Range Checks
- 17.2.1. Sensor Outputs
- 17.2.2. Navigation Solution
- 17.2.3. Kalman Filter Estimates
- 17.3. Kalman Filter Measurement Innovations
- 17.3.1. Innovation Filtering
- 17.3.2. Innovation Sequence Monitoring
- 17.3.3. Remedying Biased State Estimates
- 17.4. Direct Consistency Checks
- 17.4.1. Measurement Consistency Checks and RAIM
- 17.4.2. Parallel Solutions
- 17.5. Infrastructure-Based Integrity Monitoring
- 17.6. Solution Protection and Performance Requirements
- 17.7. Testing
- 17.7.1. Field Trials
- 17.7.2. Recorded Data Testing
- 17.7.3. Laboratory Testing
- 17.7.4. Software Simulation
- References
- ch. 18 Applications and Future Trends
- 18.1. Design and Development
- 18.2. Aviation
- 18.3. Guided Weapons and Small UAVs
- 18.4. Land Vehicle Applications
- 18.5. Rail Navigation
- 18.6. Marine Navigation
- 18.7. Underwater Navigation
- 18.8. Spacecraft Navigation
- 18.9. Pedestrian Navigation
- 18.10. Other Applications
- 18.11. Future Trends
- References.