Non-Cooperative Target Tracking, Fusion and Control Algorithms and A
This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of adva
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Zhongliang Jing Han Pan Yuankai Li Peng Dong
Non-Cooperative Target Tracking, Fusion and Control Algorithms and Advances
Information Fusion and Data Science Series editor Henry Leung, University of Calgary, Calgary, Alberta, Canada
This book series provides a forum to systematically summarize recent developments, discoveries and progress on multi-sensor, multi-source/multi-level data and information fusion along with its connection to data-enabled science. Emphasis is also placed on fundamental theories, algorithms and real-world applications of massive data as well as information processing, analysis, fusion and knowledge generation. The aim of this book series is to provide the most up-to-date research results and tutorial materials on current topics in this growing field as well as to stimulate further research interest by transmitting the knowledge to the next generation of scientists and engineers in the corresponding fields. The target audiences are graduate students, academic scientists as well as researchers in industry and government, related to computational sciences and engineering, complex systems and artificial intelligence. Formats suitable for the series are contributed volumes, monographs and lecture notes.
More information about this series at http://www.springer.com/series/15462
Zhongliang Jing • Han Pan • Yuankai Li Peng Dong
Non-Cooperative Target Tracking, Fusion and Control Algorithms and Advances
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Zhongliang Jing School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai, China
Han Pan School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai, China
Yuankai Li University of Electronic Science and Technology of China Chengdu, Sichuan, China
Peng Dong School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai, Shanghai, China
ISSN 2510-1528 ISSN 2510-1536 (electronic) Information Fusion and Data Science ISBN 978-3-319-90715-4 ISBN 978-3-319-90716-1 (eBook) https://doi.org/10.1007/978-3-319-90716-1 Library of Congress Control Number: 2018942611 © Springer International Publishing AG, part of Springer Nature 2018 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
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