| Description |
1 online resource |
| Series |
Devices, Circuits, and Systems |
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Devices, circuits, and systems.
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| Contents |
Cover; Half Title; Title Page; Copyright Page; Dedication; Contents; Preface; Editors; Contributors; Historical Note; Section I: Preliminaries on Attitude Representations and Rotations; Chapter 1: What Are Quaternions and Why Haven't I Heard of Them?; Chapter 2: Rotation in 3D Space; Chapter 3: Attitude Parametrization, Kinematics, and Dynamics; Section II: Multisensor Filtering for Attitude Estimation: Theories and Applications; Chapter 4: Stable Estimation of Rigid Body Motion Based on the Lagrange-d'Alembert Principle |
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Chapter 5: The Additive and Multiplicative Approaches to Quaternion Kalman FilteringChapter 6: Spacecraft Attitude Determination; Chapter 7: How to Deal with the External Acceleration When Estimating the Attitude Using Inertial Measurement Units: A Linear Kalman-Based Filtering Approach; Chapter 8: From Attitude Estimation to Pose Estimation Using Dual Quaternions; Chapter 9: Distributed Estimation for Spatial Rigid Motion Based on Dual Quaternions |
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Chapter 10: A Quaternion Orientation from Earth Field Observations Using the Algebraic Quaternion Algorithm: Analysis and Applications in Fusion AlgorithmsChapter 11: Recent Nonlinear Attitude Estimation Algorithms; Chapter 12: Low Complexity Sensor Fusion Solution for Accurate Estimation of Gravity and Linear Acceleration; Chapter 13: Deterministic Attitude Estimation; Chapter 14: Attitude Estimations with Intermittent Observations; Chapter 15: Estimation of Attitude from a Single-Direction Sensor; Chapter 16: Cooperative Attitude Estimation Based on Remote-Access Observations |
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Chapter 17: Nonlinear Observer for Attitude, Position, and Velocity Theory and ExperimentsChapter 18: Spacecraft Attitude Estimation Using Sparse Grid Quadrature Filtering; Chapter 19: Attitude Estimation for Small, Low-Cost UAVs: A Tutorial Approach; Chapter 20: 3D Orientation Estimation Using Wearable MEMS Inertial/Magnetic Sensors; Chapter 21: Adaptive Data Fusion of Multiple Sensors for Vehicle Pose Estimation; Chapter 22: Optimal Invariant Observers Theory for Nonlinear State Estimation |
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Chapter 23: Design and Implementation of Low-Cost Attitude Heading References Systems for Micro Aerial VehiclesChapter 24: Small Satellite Attitude Determination; Chapter 25: A Hybrid Data Fusion Approach for Robust Attitude Estimation; Chapter 26: Integration of Single-Frame and Filtering Methods for Nanosatellite Attitude Estimation; Chapter 27: Ego-Motion Tracking in Dynamic Environments Using Wearable Visual-Inertial Sensors; Chapter 28: Attitude Estimation for a Small-Scale Flybarless Helicopter; Chapter 29: A Comparison of Multisensor Attitude Estimation Algorithms |
| Summary |
There has been an increasing interest in multi-disciplinary research on multisensor attitude estimation technology driven by its versatility and diverse areas of application, such as sensor networks, robotics, navigation, video, biomedicine, etc. Attitude estimation consists of the determination of rigid bodies' orientation in 3D space. This research area is a multilevel, multifaceted process handling the automatic association, correlation, estimation, and combination of data and information from several sources. Data fusion for attitude estimation is motivated by several issues and problems, such as data imperfection, data multi-modality, data dimensionality, processing framework, etc. While many of these problems have been identified and heavily investigated, no single data fusion algorithm is capable of addressing all the aforementioned challenges. The variety of methods in the literature focus on a subset of these issues to solve, which would be determined based on the application in hand. Historically, the problem of attitude estimation has been introduced by Grace Wahba in 1965 within the estimate of satellite attitude and aerospace applications. This book intends to provide the reader with both a generic and comprehensive view of contemporary data fusion methodologies for attitude estimation, as well as the most recent researches and novel advances on multisensor attitude estimation task. It explores the design of algorithms and architectures, benefits, and challenging aspects, as well as a broad array of disciplines, including: navigation, robotics, biomedicine, motion analysis, etc. A number of issues that make data fusion for attitude estimation a challenging task, and which will be discussed through the different chapters of the book, are related to: 1) The nature of sensors and information sources (accelerometer, gyroscope, magnetometer, GPS, inclinometer, etc.); 2) The computational ability at the sensors; 3) The theoretical developments and convergence proofs; 4) The system architecture, computational resources, fusion level |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Detectors.
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Electronics in navigation.
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Sensor networks.
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TECHNOLOGY & ENGINEERING -- Technical & Manufacturing Industries & Trades.
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Detectors
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Electronics in navigation
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Sensor networks
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| Form |
Electronic book
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| Author |
Fourati, Hassen, editor
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Belkhiat, Djamel Eddine Chouaib, editor
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| ISBN |
1498745806 |
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9781498745802 |
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9781315351759 |
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1315351757 |
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9781315332710 |
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131533271X |
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9781315368795 |
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131536879X |
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