Principles of GNSS, inertial, and multisensor integrated navigation systems /

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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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Groves, Paul D. (Paul David) (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boston : Artech House, [2013]
Edición:Second edition.
Colección:GNSS technology and applications series.
Temas:
Global Positioning System.
Artificial satellites in navigation.
Inertial navigation systems.
Navigation > Technological innovations.
GPS.
Satellites artificiels en navigation.
Navigation > Innovations.
TECHNOLOGY & ENGINEERING > Engineering (General)
Artificial satellites in navigation
Global Positioning System
Inertial navigation systems
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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.

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