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

  • 6h 23m
  • Patrick Y. C. Hwang, Robert Grover Brown
  • John Wiley & Sons (US)
  • 2012

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.

In this Book

  • Probability and Random Variables—A Review
  • Mathematical Description of Random Signals
  • Linear Systems Response, State-Space Modeling, and Monte Carlo Simulation
  • Discrete Kalman Filter Basics
  • Intermediate Topics on Kalman Filtering
  • Smoothing and Further Intermediate Topics
  • Linearization, Nonlinear Filtering, and Sampling Bayesian Filters
  • The “Go-Free” Concept, Complementary Filter, and Aided Inertial Examples
  • Kalman Filter Applications to the GPS and other Navigation Systems