Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises

Robert Grover Brown

ISBN 10: 0470609699 / ISBN 13: 9780470609699

Published by Wiley & Sons, 2012

About this Item

Neuware - The Fourth Edition to the Introduction of Random Signals and Applied Kalman Filtering is updated to cover innovations in the Kalman filter algorithm and the proliferation of Kalman filtering applications from the past decade. The text updates both the research advances in variations on the Kalman filter algorithm and adds a wide range of new application examples. Several chapters include a significant amount of new material on applications such as simultaneous localization and mapping for autonomous vehicles, inertial navigation systems and global satellite navigation systems.

Seller Inventory # 9780470609699

Bibliographic Details

• Title: Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises
• Publisher: Wiley & Sons
• Publication Date: 2012
• Language: English
• ISBN 10: 0470609699
• ISBN 13: 9780470609699
• Binding: Buch
• Edition: 4th Edition
• Condition: Neu
• Dimensions: 253W x 185H x 18D millimeters 253 millimeters width by 185 millimeters height by 18 millimeters depth
• Weight: 698 grams

About this title

Synopsis

Introduction to Random Signals and Applied Kalman Filtering: With MATLAB Exercises, 4th Edition

Advances in computers and personal navigation systems have greatly expanded the applications of Kalman filters. A Kalman filter uses information about noise and system dynamics to reduce uncertainty from noisy measurements. Common applications of Kalman filters include such fast-growing fields as autopilot systems, battery state of charge (SoC) estimation, brain-computer interface, dynamic positioning, inertial guidance systems, radar tracking, and satellite navigation systems.

Brown and Hwang's bestselling textbook introduces the theory and applications of Kalman filters for senior undergraduates and graduate students. This revision updates both the research advances in variations on the Kalman filter algorithm and adds a wide range of new application examples. The book emphasizes the application of computational software tools such as MATLAB. The companion website includes M-files to assist students in applying MATLAB to solving end-of-chapter homework problems.

About the Author

Robert Grover Brown, Professor Emeritus, Iowa State University.

Patrick Y. C. Hwang, Rockwell Collins, Inc.