Kalman Filtering: Theory and Practice Using MATLAB

Grewal, Mohinder S. und Angus P. Andrews:

ISBN 10: 0470173661 / ISBN 13: 9780470173664

Verlag: John Wiley & Sons, 2008

Beschreibung

592 Seiten Ausgetragenes Bibliotheksexemplar, Buch in sehr gutem Zustand. MIG-08-03BH Sprache: Englisch Gewicht in Gramm: 945.

Bestandsnummer des Verkäufers 1837092

Bibliografische Details

• Titel: Kalman Filtering: Theory and Practice Using MATLAB
• Verlag: John Wiley & Sons
• Veröffentlichungsdatum: 2008
• Sprache: Englisch
• ISBN-10: 0470173661
• ISBN-13: 9780470173664
• Bindung: 8° Gebundene Ausgabe
• Ausgabe: Auflage: 3. Auflage.
• Zustand: Sehr gut
• Verkäuferkataloge:
  • Technik

Über diesen Titel

Inhaltsangabe

This book provides readers with a solid introduction to the theoretical and practical aspects of Kalman filtering. It has been updated with the latest developments in the implementation and application of Kalman filtering, including adaptations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation. All software is provided in MATLAB, giving readers the opportunity to discover how the Kalman filter works in action and to consider the practical arithmetic needed to preserve the accuracy of results. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Über die Autorin bzw. den Autor

Mohinder S. Grewal, PhD, PE, is Professor of Electrical Engineering in the College of Engineering and Computer Science at California State University, Fullerton. He has more than thirty-five years of experience in inertial navigation and control, and his mechanizations are currently used in commercial and military aircraft, surveillance satellites, missile and radar systems, freeway traffic control, and the Global Navigation Satellite System. Angus P. Andrews, PhD, is a retired senior scientist from the Rockwell Science Center. His experience with aerospace systems analysis and design using Kalman filters began with his involvement in the Apollo moon project, and he is credited with the discovery of unknown landmark tracking as an orbital navigation method.