"Intuitive understanding of Kalman filtering with MATLAB"/
"Intuitive understanding of Kalman filtering with MATLAB"/
by Armando Barreto and et al.
- 1st ed.
- CRC Press, Boca Raton, FL: 2021
- xviii, 229 p.: ill.; 23 cm.
Includes bibliographical references and indexes.
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
The emergence of affordable micro sensors, such as MEMS Inertial Measurement Systems, which are being applied in embedded systems and Internet-of-Things devices, has brought techniques such as Kalman Filtering, capable of combining information from multiple sensors or sources, to the interest of students and hobbyists.
9780367191337
Computer Graphics Game Programming & Design
MATLAB
Kalman filtering
Numerical analysis Computer programs
006.42 / BAI
Includes bibliographical references and indexes.
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
The emergence of affordable micro sensors, such as MEMS Inertial Measurement Systems, which are being applied in embedded systems and Internet-of-Things devices, has brought techniques such as Kalman Filtering, capable of combining information from multiple sensors or sources, to the interest of students and hobbyists.
9780367191337
Computer Graphics Game Programming & Design
MATLAB
Kalman filtering
Numerical analysis Computer programs
006.42 / BAI