The Kalman Filter: Introduction

by Andrew MacLean

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.

• Format: Paperback
• Language: English
• ISBN: B09MDY449W
• ISBN13: 9798775161026
• Release Date: November 2021
• Publisher: Independently Published
• Length: 188 Pages
• Weight: 0.57 lbs.
• Dimensions: 0.4" x 6.0" x 9.0"