The Kalman Filter: Introduction

by Andrew MacLean

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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"

Related Subjects

Engineering Technology

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The Kalman Filter: Introduction

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