ABSTRACT
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. This will book will develop just the necessary background concepts, helping a much wider audience of readers develop an understanding and intuition that will enable them to follow the explanation for the Kalman Filtering algorithm
TABLE OF CONTENTS
part I|52 pages
Background
part II|48 pages
Where Does Kalman Filtering Apply and What Does It Intend to Do?
chapter Chapter 7|14 pages
Reflecting on the Meaning and Evolution of the Entities in the Kalman Filter Algorithm
part III|50 pages
Examples in MATLAB®
part IV|45 pages
Kalman Filtering Application to IMUs