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Nonlinear kalman filtering for multi-sensor navigation of unmanned aerial vehicles : application to guidance and navigation of unmanned aerial vehicles flying in a complex environment /
Nonlinear Kalman Filtering for Multi-Sensor Navigation of Unmanned Aerial Vehicles covers state estimation development approaches for Mini-UAV. The book focuses on Kalman filtering technics for UAV design, proposing a new design methodology and case study related to inertial navigation systems for d...
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| Main Author: | |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Amsterdam :
Elsevier,
2018.
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| Subjects: | |
| Online Access: |
Full text (Wentworth users only) |
MARC
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| 100 | 1 | |a Condomines, Jean-Philippe, |e author. | |
| 245 | 1 | 0 | |a Nonlinear kalman filtering for multi-sensor navigation of unmanned aerial vehicles : |b application to guidance and navigation of unmanned aerial vehicles flying in a complex environment / |c Jean-Philippe Condomines. |
| 264 | 1 | |a Amsterdam : |b Elsevier, |c 2018. | |
| 300 | |a 1 online resource : |b illustrations (some color) | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a Nonlinear Kalman Filtering for Multi-Sensor Navigation of Unmanned Aerial Vehicles covers state estimation development approaches for Mini-UAV. The book focuses on Kalman filtering technics for UAV design, proposing a new design methodology and case study related to inertial navigation systems for drones. Both simulation and real experiment results are presented, thus showing new and promising perspectives. | ||
| 588 | 0 | |a Print version record. | |
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| 650 | 0 | |a Drone aircraft |x Control systems. |0 sh2002000348 | |
| 650 | 0 | |a Kalman filtering. |0 sh 85071360 | |
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| 880 | 0 | |6 505-00/(S |a <p>1. Introduction to Aerial Robotics 2. The State of the Art 3. Inertial Navigation Models 4. The IUKF and π-IUKF Algorithms 5. Methodological Validation, Experiments and Results </p> | |
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