The Kalman Filter: Introduction

This introduction to the Kalman filter reviews linear systems, probability, random processes, estimation, digital filters, and Markov processes. This sets the context for the derivation of the scalar and vector Kalman filter. Examples, coded in the C language, are presented and discussed.

• | Author: Andrew MacLean
• | Publisher: Independently Published
• | Publication Date: Nov 30, 2021
• | Number of Pages: 188 pages
• | Binding: Paperback or Softback
• | ISBN-13: 9798775161026