Open access peer-reviewed Edited Volume

Introduction and Implementations of the Kalman Filter

Edited by Felix Govaers

Fraunhofer Institute for Communication, Information Processing and Ergonomics, Germany

Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some "awareness" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.

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Introduction and Implementations of the Kalman FilterEdited by Felix Govaers

Published: May 22nd 2019

DOI: 10.5772/intechopen.75731

ISBN: 978-1-83880-537-1

Print ISBN: 978-1-83880-536-4

eBook (PDF) ISBN: 978-1-83880-739-9

Copyright year: 2019

Books open for chapter submissions

1731 Total Chapter Downloads

1 Crossref Citations

chaptersDownloads

Open access peer-reviewed

1. Introductory Chapter: Kalman Filter - The Working Horse of Object Tracking Systems Nowadays

By Felix Govaers

124

Open access peer-reviewed

2. Introduction to Kalman Filter and Its Applications

By Youngjoo Kim and Hyochoong Bang

874

Open access peer-reviewed

3. Tuning of the Kalman Filter Using Constant Gains

By Mudambi R. Ananthasayanam

318

Open access peer-reviewed

4. Statically Fused Converted Measurement Kalman Filters

By Gongjian Zhou and Zhengkun Guo

121

Open access peer-reviewed

5. A Scalable, FPGA-Based Implementation of the Unscented Kalman Filter

By Jeremy Soh and Xiaofeng Wu

209

Open access peer-reviewed

6. Novel Direct and Accurate Identification of Kalman Filter for General Systems Described by a Box-Jenkins Model

By Rajamani Doraiswami and Lahouari Cheded

85

Edited Volume and chapters are indexed in

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  • CNKI
  • IET Inspec

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