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Multi Sensor Data Fusion


Multi Sensor Data Fusion
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Mathematical Techniques In Multisensor Data Fusion


Mathematical Techniques In Multisensor Data Fusion
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Author : David Lee Hall
language : en
Publisher: Artech House
Release Date : 2004

Mathematical Techniques In Multisensor Data Fusion written by David Lee Hall and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.


Since the publication of the first edition of this book, advances in algorithms, logic and software tools have transformed the field of data fusion. The latest edition covers these areas as well as smart agents, human computer interaction, cognitive aides to analysis and data system fusion control. data fusion system, this book guides you through the process of determining the trade-offs among competing data fusion algorithms, selecting commercial off-the-shelf (COTS) tools, and understanding when data fusion improves systems processing. Completely new chapters in this second edition explain data fusion system control, DARPA's recently developed TRIP model, and the latest applications of data fusion in data warehousing and medical equipment, as well as defence systems.



Multi Sensor Data Fusion


Multi Sensor Data Fusion
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Author : H.B. Mitchell
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-13

Multi Sensor Data Fusion written by H.B. Mitchell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-13 with Technology & Engineering categories.


The purpose of this book is to provide an introduction to the theories and techniques of multi-sensor data fusion. The book has been designed as a text for a one-semester graduate course in multi-sensor data fusion. It should also be useful to advanced undergraduates in electrical engineering or computer science who are studying data fusion for the ?rst time and to practising en- neers who wish to apply the concepts of data fusion to practical applications. The book is intended to be largely self-contained in so far as the subject of multi-sensor data fusion is concerned, although some prior exposure to the subject may be helpful to the reader. A clear understanding of multi-sensor data fusion can only be achieved with the use of a certain minimum level of mathematics.Itisthereforeassumedthatthereaderhasareasonableworking knowledge of the basic tools of linear algebra, calculus and simple probability theory. More speci?c results and techniques which are required are explained in the body of the book or in appendices which are appended to the end of the book.



Multi Sensor Data Fusion With Matlab


Multi Sensor Data Fusion With Matlab
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Author : Jitendra R. Raol
language : en
Publisher: CRC Press
Release Date : 2009-12-16

Multi Sensor Data Fusion With Matlab written by Jitendra R. Raol and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-16 with Technology & Engineering categories.


Using MATLAB examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly



Data Fusion Concepts And Ideas


Data Fusion Concepts And Ideas
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Author : H B Mitchell
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-09

Data Fusion Concepts And Ideas written by H B Mitchell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-09 with Technology & Engineering categories.


This textbook provides a comprehensive introduction to the concepts and idea of multisensor data fusion. It is an extensively revised second edition of the author's successful book: "Multi-Sensor Data Fusion: An Introduction" which was originally published by Springer-Verlag in 2007. The main changes in the new book are: New Material: Apart from one new chapter there are approximately 30 new sections, 50 new examples and 100 new references. At the same time, material which is out-of-date has been eliminated and the remaining text has been rewritten for added clarity. Altogether, the new book is nearly 70 pages longer than the original book. Matlab code: Where appropriate we have given details of Matlab code which may be downloaded from the worldwide web. In a few places, where such code is not readily available, we have included Matlab code in the body of the text. Layout. The layout and typography has been revised. Examples and Matlab code nowappear on a gray background for easy identification and advancd material is marked with an asterisk. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familarity with the basic tools of linear algebra, calculus and simple probability is recommended. Although conceptually simple, the study of mult-sensor data fusion presents challenges that are unique within the education of the electrical engineer or computer scientist. To become competent in the field the student must become familiar with tools taken from a wide range of diverse subjects including: neural networks, signal processing, statistical estimation, tracking algorithms, computer vision and control theory. All too often, the student views multi-sensor data fusion as a miscellaneous assortment of different processes which bear no relationship to each other. In contrast, in this book the processes are unified by using a common statisticalframework. As a consequence, the underlying pattern of relationships that exists between the different methodologies is made evident. The book is illustrated with many real-life examples taken from a diverse range of applications and contains an extensive list of modern references.



Handbook Of Multisensor Data Fusion


Handbook Of Multisensor Data Fusion
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Author : Martin Liggins II
language : en
Publisher: CRC Press
Release Date : 2017-01-06

Handbook Of Multisensor Data Fusion written by Martin Liggins II and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-06 with Technology & Engineering categories.


In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition represents the most current concepts and theory as information fusion expands into the realm of network-centric architectures. It reflects new developments in distributed and detection fusion, situation and impact awareness in complex applications, and human cognitive concepts. With contributions from the world’s leading fusion experts, this second edition expands to 31 chapters covering the fundamental theory and cutting-edge developments that are driving this field. New to the Second Edition— · Applications in electromagnetic systems and chemical and biological sensors · Army command and combat identification techniques · Techniques for automated reasoning · Advances in Kalman filtering · Fusion in a network centric environment · Service-oriented architecture concepts · Intelligent agents for improved decision making · Commercial off-the-shelf (COTS) software tools From basic information to state-of-the-art theories, this second edition continues to be a unique, comprehensive, and up-to-date resource for data fusion systems designers.



Multi Sensor Data Fusion With Matlab


Multi Sensor Data Fusion With Matlab
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Author : Jitendra R. Raol
language : en
Publisher: CRC Press
Release Date : 2009-12-16

Multi Sensor Data Fusion With Matlab written by Jitendra R. Raol and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-16 with Technology & Engineering categories.


Using MATLAB® examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly for aerospace applications, although the methods can also be applied to systems in other areas, such as biomedicine, military defense, and environmental engineering. After presenting several useful strategies and algorithms for DF and tracking performance, the book evaluates DF algorithms, software, and systems. It next covers fuzzy logic, fuzzy sets and their properties, fuzzy logic operators, fuzzy propositions/rule-based systems, an inference engine, and defuzzification methods. It develops a new MATLAB graphical user interface for evaluating fuzzy implication functions, before using fuzzy logic to estimate the unknown states of a dynamic system by processing sensor data. The book then employs principal component analysis, spatial frequency, and wavelet-based image fusion algorithms for the fusion of image data from sensors. It also presents procedures for combing tracks obtained from imaging sensor and ground-based radar. The final chapters discuss how DF is applied to mobile intelligent autonomous systems and intelligent monitoring systems. Fusing sensors’ data can lead to numerous benefits in a system’s performance. Through real-world examples and the evaluation of algorithmic results, this detailed book provides an understanding of MSDF concepts and methods from a practical point of view. Select MATLAB programs are available for download on www.crcpress.com



Multisensor Data Fusion


Multisensor Data Fusion
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Author : Hassen Fourati
language : en
Publisher: CRC Press
Release Date : 2017-12-19

Multisensor Data Fusion written by Hassen Fourati and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Technology & Engineering categories.


Multisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world’s leading data fusion researchers and academicians, this authoritative book: Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors Describes new materials and achievements in optimal fusion and multisensor filters Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.



Multi Sensor Information Fusion


Multi Sensor Information Fusion
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Author : Xue-Bo Jin
language : en
Publisher: MDPI
Release Date : 2020-03-23

Multi Sensor Information Fusion written by Xue-Bo Jin and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-23 with Technology & Engineering categories.


This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.



Multisensor Fusion


Multisensor Fusion
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Author : Anthony K. Hyder
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-07-31

Multisensor Fusion written by Anthony K. Hyder and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-07-31 with Computers categories.


Proceedings of the NATO Advanced Study Institute on Multisensor Data Fusion, held in Pitlochry, Perthshire, Scotland, June 25-July 7, 2000



New Data Fusion Algorithms For Distributed Multi Sensor Multi Target Environments


New Data Fusion Algorithms For Distributed Multi Sensor Multi Target Environments
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Author : Ashraf Mamdouh Abdel Aziz
language : en
Publisher:
Release Date : 1999-09-01

New Data Fusion Algorithms For Distributed Multi Sensor Multi Target Environments written by Ashraf Mamdouh Abdel Aziz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-09-01 with categories.


Multisensor data fusion combines data from multiple sensor systems to achieve improved performance and provide more inferences than could be achieved using a single sensor system. One of the most important aspects of data fusion is data association. This dissertation develops new algorithms for data association, including measurement to track association, track to track association and track fusion, in distributed multisensor multitarget environment with overlapping sensor coverage. The performance of the proposed algorithms is compared to that of existing techniques. Computational complexity analysis is also presented. Numerical results based on Monte Carlo simulations and real data collected from the United States Coast Guard Vessel Traffic Services system are presented. The results show that the proposed algorithms reduce the computational complexity and achieve considerable performance improvement over those previously reported in the literature.