Kalman Filter

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Kalman Filter

Introduction to State Estimation and Its Application for Embedded Systems

Vehicle and transport manufacturing industries Probability and statistics Stochastics Electrical engineering Automatic control engineering Computer hardware Image processing

Authors: Reiner Marchthaler, Sebastian Dingler

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Collection: Intelligent Technologies and Robotics

Language: English

Published by: Springer

Published on: 23rd February 2026

Format: LCP-protected ePub

ISBN: 9783658503888


Introduction to Kalman Filtering

This textbook presents the theory of Kalman filtering in an easy-to-understand way. The authors provide an introduction to Kalman filters and their application in embedded systems. In addition, the design of Kalman filters is demonstrated using concrete practical examples – individual steps are explained in detail throughout the book.

Importance of Kalman Filters

Kalman filters are the method of choice for eliminating interference signals from sensor data. This is particularly important because many technical systems obtain their process-relevant information via sensors. However, every sensor measurement contains errors due to various factors. If a system were to operate solely based on these inaccurate sensor readings, many applications—such as navigation systems or autonomous systems—would not be feasible.

Target Audience

The book is suitable for interested bachelor's and master's students in the fields of computer science, mechanical engineering, electrical engineering, and mechatronics. It is also a valuable resource for engineers and researchers who want to use a Kalman filter, for example, for data fusion or the estimation of unknown variables in real-time applications.

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