Αποτελέσματα αναζήτησης - "algorithms"

Quantitative evaluation of HIV prevention programs

Πίνακας περιεχομένων: “…Development and Validation of a Serologic Testing Algorithm for Recent HIV Seroconversion GlenA. Satten, -- Robert S. …”
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Sustainable production automation / από Li, Jingshan, Dr, Lennartson, Bengt, 1956-, Tang, Ying (Gina), Biller, Stephan, Matta, Andrea

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Sustainable production automation / από Li, Jingshan, Dr, Lennartson, Bengt, 1956-, Tang, Ying (Gina), Biller, Stephan, Matta, Andrea

An electronic book accessible through the World Wide Web; click to view

Designs and prototypes of mobile robots /

Πίνακας περιεχομένων: “…Exoskeletons and bipeds / Qiang Huang and Zhangguo Yu -- 2.1 Exoskeletons -- 2.1.1 History and overview -- 2.1.2 Mechanism design principles -- 2.1.3 Sensing and control algorithm -- 2.1.4 Actuators and portable power supply -- 2.2 Bipeds -- 2.2.1 History and overview -- 2.2.2 Mechanism design -- 2.2.3 Motion planning -- 2.2.4 Stability control -- 2.2.5 Control system -- 2.2.6 Biped walking -- 2.3 Conclusions -- 2.4 References --…”
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Designs and prototypes of mobile robots /

Πίνακας περιεχομένων: “…Exoskeletons and bipeds / Qiang Huang and Zhangguo Yu -- 2.1 Exoskeletons -- 2.1.1 History and overview -- 2.1.2 Mechanism design principles -- 2.1.3 Sensing and control algorithm -- 2.1.4 Actuators and portable power supply -- 2.2 Bipeds -- 2.2.1 History and overview -- 2.2.2 Mechanism design -- 2.2.3 Motion planning -- 2.2.4 Stability control -- 2.2.5 Control system -- 2.2.6 Biped walking -- 2.3 Conclusions -- 2.4 References --…”
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Principles of GNSS, inertial, and multisensor integrated navigation systems / από Groves, Paul D. (Paul David)

Πίνακας περιεχομένων: “…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.…”
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Principles of GNSS, inertial, and multisensor integrated navigation systems / από Groves, Paul D. (Paul David)

Πίνακας περιεχομένων: “…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.…”
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Aerospace sensors από Nebylov, A. V. (Aleksandr Vladimirovich)

Πίνακας περιεχομένων: “…Principles and examples of sensor integration -- 9.1 Sensor systems -- 9.1.1 The sensor system concept -- 9.1.2 Joint processing of readings from identical sensors -- 9.1.3 Joint processing of readings from cognate sensors with different measurement ranges -- 9.1.4 Joint processing of diverse sensors readings -- 9.1.5 Linear and nonlinear sensor integration algorithms -- 9.2 Fundamentals of integrated measuring system synthesis -- 9.2.1 Synthesis problem statement -- 9.2.2 Classes of dynamic system realization -- 9.2.3 Measurement accuracy indices -- 9.2.4 Excitation properties -- 9.2.5 Objective functions for robust system optimisation -- 9.2.6 Methods of dynamic system accuracy index analysis under excitation with given numerical characteristics of derivatives -- 9.2.6.1 Estimation of error variance -- 9.2.6.2 Example of error variance analysis -- 9.2.6.3 Use of equivalent harmonic excitation -- 9.2.6.4 Estimation of error maximal value -- 9.2.7 System optimization under maximum accuracy criteria -- 9.2.8 Procedures for the dimensional reduction of a measuring system -- 9.2.8.1 Determination of an optimal set of sensors -- 9.2.8.2 Analysis of the advantages of invariant system construction -- 9.2.8.3 Advantages of the zeroing of several system parameters -- 9.2.9 Realization and simulation of integration algorithms -- 9.3 Examples of two-component integrated navigation systems -- 9.3.1 Noninvariant robust integrated speed meter -- 9.3.2 Integrated radio-inertial measurement -- 9.3.3 Airborne gravimeter integration -- 9.3.4 The orbital verticant -- References --…”
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Aerospace sensors από Nebylov, A. V. (Aleksandr Vladimirovich)

Πίνακας περιεχομένων: “…Principles and examples of sensor integration -- 9.1 Sensor systems -- 9.1.1 The sensor system concept -- 9.1.2 Joint processing of readings from identical sensors -- 9.1.3 Joint processing of readings from cognate sensors with different measurement ranges -- 9.1.4 Joint processing of diverse sensors readings -- 9.1.5 Linear and nonlinear sensor integration algorithms -- 9.2 Fundamentals of integrated measuring system synthesis -- 9.2.1 Synthesis problem statement -- 9.2.2 Classes of dynamic system realization -- 9.2.3 Measurement accuracy indices -- 9.2.4 Excitation properties -- 9.2.5 Objective functions for robust system optimisation -- 9.2.6 Methods of dynamic system accuracy index analysis under excitation with given numerical characteristics of derivatives -- 9.2.6.1 Estimation of error variance -- 9.2.6.2 Example of error variance analysis -- 9.2.6.3 Use of equivalent harmonic excitation -- 9.2.6.4 Estimation of error maximal value -- 9.2.7 System optimization under maximum accuracy criteria -- 9.2.8 Procedures for the dimensional reduction of a measuring system -- 9.2.8.1 Determination of an optimal set of sensors -- 9.2.8.2 Analysis of the advantages of invariant system construction -- 9.2.8.3 Advantages of the zeroing of several system parameters -- 9.2.9 Realization and simulation of integration algorithms -- 9.3 Examples of two-component integrated navigation systems -- 9.3.1 Noninvariant robust integrated speed meter -- 9.3.2 Integrated radio-inertial measurement -- 9.3.3 Airborne gravimeter integration -- 9.3.4 The orbital verticant -- References --…”
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Introduction to ALGOL / από Baumann, Richard

Introduction to ALGOL / από Baumann, Richard

Advanced dynamic-system simulation model replication and Monte Carlo studies / από Korn, Granino A. (Granino Arthur), 1922-

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Advanced dynamic-system simulation model replication and Monte Carlo studies / από Korn, Granino A. (Granino Arthur), 1922-

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Modem theory an introduction to telecommunications / από Blahut, Richard E.

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Modem theory an introduction to telecommunications / από Blahut, Richard E.

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Financial Innovation

Open Access

Financial Innovation

Open Access

Big Data Analytics

Open Access

Big Data Analytics

Open Access

Venice Variations : Tracing the Architectural Imagination από Psarra, Sophia

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