Introduction to random signals and applied Kalman filtering :
General Material Designation
[Book]
Other Title Information
with MATLAB exercises /
First Statement of Responsibility
Robert Grover Brown, Patrick Y.C. Hwang
EDITION STATEMENT
Edition Statement
4th ed
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Hoboken, NJ :
Name of Publisher, Distributor, etc.
John Wiley,
Date of Publication, Distribution, etc.
c2012
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xii, 383 p. :
Other Physical Details
ill. ;
Dimensions
26 cm
GENERAL NOTES
Text of Note
Machine generated contents note: PART 1: RANDOM SIGNALS BACKGROUND Chapter 1 Probability and Random Variables: A Review Chapter 2 Mathematical Description of Random Signals Chapter 3 Linear Systems Response, State-space Modeling and Monte Carlo Simulation PART 2: KALMAN FILTERING AND APPLICATIONS Chapter 4 Discrete Kalman Filter Basics Chapter 5 Intermediate Topics on Kalman Filtering Chapter 6 Smoothing and Further Intermediate Topics Chapter 7 Linearization, Nonlinear Filtering and Sampling Bayesian Filters Chapter 8 the "Go-Free" Concept, Complementary Filter and Aided Inertial Examples Chapter 9 Kalman Filter Applications to the GPS and Other Navigation Systems APPENDIX A. Laplace and Fourier Transforms APPENDIX B. The Continuous Kalman Filter
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index
CONTENTS NOTE
Text of Note
Machine generated contents note: PART 1. RANDOM SIGNALS BACKGROUND Chapter 1 Probability and Random Variables: A Review Chapter 2. Mathematical Description of Random Signals Chapter 3. Linear Systems Response, State-Space Modeling, and Monte Carlo Simulation -- PART 2. KALMAN FILTERING AND APPLICATIONS Chapter 4. Discrete Kalman Filter Basics Chapter 5. Intermediate Topics on Kalman Filtering Chapter 6. Smoothing and Further Intermediate Topics Chapter 7. Linearization, Nonlinear Filtering, and Sampling Bayesian Filters Chapter 8. The "Go-Free" Concept, Complementary Filter, and Aided Inertial Examples Chapter 9. Kalman Filter Applications to the GPS and Other Navigation Systems APPENDIX A. Laplace and Fourier Transforms APPENDIX B. The Continuous Kalman Filter
8
SUMMARY OR ABSTRACT
Text of Note
"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"--Provided by publisher