Kalman Fusion Estimation for WSNs with Nonuniform Estimation Rates
As mentioned in Chap. 2 , developing energy-efficient algorithms for WSN-based estimation is of great practical significance since the sensor nodes are usually constrained in energy. As usually did in WSNs, one may purposively close the sensor nodes to s
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Distributed Fusion Estimation for Sensor Networks with Communication Constraints
Distributed Fusion Estimation for Sensor Networks with Communication Constraints
Wen-An Zhang • Bo Chen • Haiyu Song • Li Yu
Distributed Fusion Estimation for Sensor Networks with Communication Constraints
123
Wen-An Zhang Department of Automation Zhejiang University of Technology Hangzhou, China
Bo Chen Department of Automation Zhejiang University of Technology Hangzhou, China
Haiyu Song Zhejiang Uni. of Finance & Economics Hangzhou, China
Li Yu Zhejiang University of Technology Hangzhou, China
ISBN 978-981-10-0793-4 DOI 10.1007/978-981-10-0795-8
ISBN 978-981-10-0795-8 (eBook)
Jointly published with Science Press, Beijing ISBN: 978-7-03-047505-3 Science Press, Beijing Library of Congress Control Number: 2016935848 © Science Press, Beijing and Springer Science+Business Media Singapore 2016 This work is subject to copyright. All rights are reserved 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, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer Science+Business Media Singapore Pte Ltd.
Preface
Advances in micro electromechanical systems and wireless technologies have allowed for the emergence of inexpensive micro-sensors with embedded processing and communication capabilities. A wireless sensor network (WSN) is a collection of these physically distributed micro-sensors communicating with one another over wireless links. In their various shapes and forms, the WSNs have greatly facilitated and enhanced the automated, remote, and intelligent monitoring of a large variety of physical systems and have found applications in various areas, such as industrial and building automation; environmental, traffic, wildlife, and health monitoring; and military surveillance. The purpose of a WSN is to provide users access to the information of interest from data gathered by spatially distributed sensors. In most applications, users are interested in a processed data that carries useful infor
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