Global Positioning Systems, Inertial Navigation, and Integration

Grewal, Mohinder S.; Weill, Lawrence R.; Andrews, Angus P.

ISBN 10: 047135032X / ISBN 13: 9780471350323

Edité par Wiley-Interscience, 2000

A propos de cet article

The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.

N° de réf. du vendeur BSM.14BGB

Détails bibliographiques

• Titre: Global Positioning Systems, Inertial Navigation, and Integration
• Éditeur: Wiley-Interscience
• Date de parution: 2000
• Langue: anglais
• ISBN à 10 chiffres: 047135032X
• ISBN à 13 chiffres: 9780471350323
• Reliure: Couverture rigide
• État de l'article: good

A propos de ce titre

Synopsis

The only comprehensive guide to Kalman filtering and its applications to real--world GPS/INS problems Written by recognized authorities in the field, this book provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary applications of Global Positioning Systems (GPS), Inertial Navigational Systems, and Kalman filters. Throughout, the focus is on solving real--world problems, with an emphasis on the effective use of state--of--the--art integration techniques for those systems, especially the application of Kalman filtering. To that end, the authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real--world situations, and provide numerous detailed application examples and practice problems, including GPS--aided INS, modeling of gyros and accelerometers, and WAAS and LAAS. Drawing upon their many years of experience with GPS, INS, and the Kalman filter, the authors present numerous design and implementation techniques not found in other professional references, including original techniques for: Representing the problem in a mathematical model Analyzing the performance of the GPS sensor as a function of model parameters Implementing the mechanization equations in numerically stable algorithms Assessing computation requirements Testing the validity of results Monitoring GPS, INS, and Kalman filter performance in operation In order to enhance comprehension of the subjects covered, the authors have included software in MATLAB, demonstrating the workings of the GPS, INS, and filter algorithms. In addition to showing the Kalman filter in action, the software also demonstrates various practical aspects of finite word length arithmetic and the need for alternative algorithms to preserve result accuracy.

À propos de l?auteur

MOHINDER S. GREWAL, PhD, PE, is Professor of Electrical Engineering in the College of Engineering and Computer Science at California State University, Fullerton. LAWRENCE R. WEILL, PhD, is Professor of Applied Mathematics in the College of Mathematics and Natural Sciences at California State University, Fullerton. ANGUS P. ANDREWS, PhD, is Senior Scientist at the Rockwell Science Center in Thousand Oaks, California.