Introduction to random signals and applied Kalman filtering : with MATLAB exercises

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 fi...

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Bibliographic Details
Other Authors: Brown, Robert Grover Author (author), Hwang, Patrick Y. C Contributor (contributor)
Format: eBook
Language:Inglés
Published: [Place of publication not identified] John Wiley 2012
Edition:4th ed
Subjects:
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629299306719
Table of Contents:
  • 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.