Kalman Filtering of Discrete Dynamic Systems
R.E. Kalman firstly presents the Kalman filter (KF), which treats the target state as a random variable based on Bayesian formulation [5 ].
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ultisensor Fusion Estimation Theory and Application
Multisensor Fusion Estimation Theory and Application
Liping Yan Lu Jiang Yuanqing Xia •
•
Multisensor Fusion Estimation Theory and Application
123
Liping Yan School of Automation Beijing Institute of Technology Beijing, China
Lu Jiang School of Artificial Intelligence Beijing Technology and Business University Beijing, China
Yuanqing Xia School of Automation Beijing Institute of Technology Beijing, China
ISBN 978-981-15-9425-0 ISBN 978-981-15-9426-7 https://doi.org/10.1007/978-981-15-9426-7
(eBook)
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
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Preface
Multisensor data fusion refers to the combination of data from multiple sensors, either of the same or different types, to achieve more specific inferences than could be achieved by using a single independent sensor. It is a rapidly developing science and technology since 1970s. With the comprehensive and rapid development of science and technology, from the initial war as the background, it has developed into various aspects of civil applications, including industrial process monitoring, industrial robots, remote sensing, drug inspection, patient care systems, financial systems, and networked control systems. The theory of multisensor optimal estimation is an important part in the field of multisensor data f
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