Intuitive Understanding of Kalman Filtering with MATLAB®

Part I Background

Chapter 1 ¿ System Models and Random Variables 3

Chapter 2 ¿ Multiple Random Sequences

Chapter 3 ¿ Conditional Probability, Bayes' Rule and Bayesian Estimation 45

Part II Where Does Kalman Filtering Apply and What Does It Intend to Do?

Chapter 4 ¿ A Simple Scenario Where Kalman

Chapter 5 ¿ General Scenario Addressed by Kalman Filtering and Specific Cases 61

Chapter 6 ¿ Arriving at the Kalman Filter Algorithm 75

Chapter 7 ¿ Reflecting on the Meaning and Evolution of the Entities in the Kalman Filter Algorithm 87

Part III Examples in MATLAB®

Chapter 8 ¿ MATLAB® Function to Implement and Exemplify the Kalman Filter 103

Chapter 9 ¿ Univariate Example of Kalman Filter in MATLAB® 113

Chapter 10 ¿ Multivariate Example of Kalman Filter in MATLAB® 131

Part IV Kalman Filtering Application to IMUs

Chapter 11 ¿ Kalman Filtering Applied to 2-Axis Attitude Estimation from Real IMU Signals 153

Chapter 12 ¿ Real-Time Kalman Filtering Application to Attitude Estimation from IMU Signals 179

APPENDIX A ¿LISTINGS OF THE FILES FOR REAL-TIME IMPLEMENTATION OF THE KALMAN

FILTER FOR ATTITUDE ESTIMATION WITH ROTATIONS IN 2 AXES, 197