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Multi Sensor Data Fusion With Matlab

Author : Jitendra R. Raol
ISBN : 1439800057
Genre : Technology & Engineering
File Size : 50. 35 MB
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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

Multi Sensor Data Fusion With Matlab

Author : Jitendra R. Raol
ISBN : 1439800030
Genre : Technology & Engineering
File Size : 41. 77 MB
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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

Multi Sensor Data Fusion

Author : H.B. Mitchell
ISBN : 9783540715597
Genre : Technology & Engineering
File Size : 69. 54 MB
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This textbook provides a comprehensive introduction to the theories and techniques of multi-sensor data fusion. It is aimed at advanced undergraduate and first-year graduate students in electrical engineering and computer science, as well as researchers and professional engineers. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familiarity with the basic tools of linear algebra, calculus and simple probability theory is recommended. Although conceptually simple, the study of multi-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 this book the processes are described using a common statistical framework. As a consequence, the underlying pattern of relationships that exists between the different methodologies is made evident.

Statistical Sensor Fusion

Author : Fredrik Gustafsson
ISBN : 9144127243
Genre :
File Size : 52. 4 MB
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Sensor fusion deals with merging information from two or more sensors, where the area of statistical signal processing provides a powerful tool­box to attack both theoretical and practical problems. The objective of this book is to explain state of the art theory and algo­rithms in statistical sensor fusion, covering estimation, detection and non­linear filtering theory with applications to localisation, navi­gation and tracking problems. The book starts with a review of the theory on linear and nonlinear estimation, with a focus on sensor network applications. Then, general nonlinear filter theory is surveyed with a particular attention to different variants of the Kalman filter and the particle filter. Complexity and implementation issues are discussed in detail. Simultaneous localisation and mapping (SLAM) is used as a challenging application area of high-dimensional nonlinear filtering problems. The book spans the whole range from mathematical foundations pro­vided in extensive appendices, to real-world problems covered in a part surveying standard sensors, motion models and applications in this field. All models and algorithms are available as object-oriented Matlab code with an extensive data file library, and the examples, which are richly used to illustrate the theory, are supplemented by fully reproducible Matlab code.

Mobile Intelligent Autonomous Systems

Author : Jitendra R. Raol
ISBN : 9781439863015
Genre : Technology & Engineering
File Size : 64. 61 MB
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Going beyond the traditional field of robotics to include other mobile vehicles, Mobile Intelligent Autonomous Systems describes important theoretical concepts, techniques, approaches, and applications that can be used to build truly mobile intelligent autonomous systems (MIAS). It offers a comprehensive treatment of robotics and MIAS, as well as related disciplines, helping readers understand the subject from a system-theoretic and practical point of view. Organized into three sections, the book progresses from conceptual foundations to MIAS and robotics systems and then examines allied technologies. With an emphasis on recent research and developments, experts from various fields cover key aspects of this rapidly emerging area, including: Path and motion planning Obstacle avoidance in a dynamic environment Direct biological-brain control of a mobile robot Sensor and image data fusion Autonomous decision making and behavior modeling in robots Hydro-MiNa robot technology Adaptive algorithms for smart antennas Control methods for autonomous micro-air vehicles Neuro-fuzzy fault-tolerant auto-landing for aircraft H-infinity filter based estimation for simultaneous localization and mapping Where relevant, concepts and theories are illustrated with block/flow diagrams and numerical simulations in MATLAB®. An integrated exploration of the theory and practice of MIAS and robotics, this is a valuable reference and recipe book for research and industry.

Multi Sensor Image Fusion And Its Applications

Author : Rick S. Blum
ISBN : 9781420026986
Genre : Technology & Engineering
File Size : 76. 97 MB
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Taking another lesson from nature, the latest advances in image processing technology seek to combine image data from several diverse types of sensors in order to obtain a more accurate view of the scene: very much the same as we rely on our five senses. Multi-Sensor Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies. After a review of state-of-the-art image fusion techniques, the book provides an overview of fusion algorithms and fusion performance evaluation. The following chapters explore recent progress and practical applications of the proposed techniques to solving problems in such areas as medical diagnosis, surveillance and biometric systems, remote sensing, nondestructive evaluation, blurred image restoration, and image quality assessment. Recognized leaders from industry and academia contribute the chapters, reflecting the latest research trends and providing useful algorithms to aid implementation. Supplying a 28-page full-color insert, Multi-Sensor Image Fusion and Its Applications clearly demonstrates the benefits and possibilities of this revolutionary development. It provides a solid knowledge base for applying these cutting-edge techniques to new challenges and creating future advances.

Multisensor Data Fusion

Author : David Hall
ISBN : 9781420038545
Genre : Technology & Engineering
File Size : 28. 97 MB
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The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolution of computers and the maturation of data fusion technology, the door to using data fusion in everyday applications is now wide open and presenting great opportunities. The Handbook of Multisensor Data Fusion provides a unique, comprehensive, and up-to-date resource for data fusion systems designers and researchers. Divided into five parts, it: offers a thorough introduction to data fusion terminology and models describes advanced techniques for data association, target tracking, and identification presents practical information on system development, including requirements analysis, systems engineering, algorithm selection, database design, human-computer interfaces, and performance assessment introduces applications from the DoD, NASA, DARPA, and condition-based monitoring of complex machinery supplies data fusion resources and Web sites The contributing authors are all recognized leaders in data fusion and have collaborated to provide what promises to be the definitive reference for this rapidly developing field. Whether you are a researcher, system designer, implementer, or student, in the Handbook of Multisensor Data Fusion you'll find everything you need, from a basic introduction and survey of data fusion technology to advanced mathematics and theory, including very practical advice on data fusion system development and implementation.

Data Fusion Mathematics

Author : Jitendra R. Raol
ISBN : 9781498721028
Genre : Mathematics
File Size : 28. 15 MB
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Fills the Existing Gap of Mathematics for Data Fusion Data fusion (DF) combines large amounts of information from a variety of sources and fuses this data algorithmically, logically and, if required intelligently, using artificial intelligence (AI). Also, known as sensor data fusion (SDF), the DF fusion system is an important component for use in various applications that include the monitoring of vehicles, aerospace systems, large-scale structures, and large industrial automation plants. Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion, and provides a proper and adequate understanding of the basic mathematics directly related to DF. The material covered can be used for evaluation of the performances of any designed and developed DF systems. It tries to answer whether unified data fusion mathematics can evolve from various disparate mathematical concepts, and highlights mathematics that can add credibility to the data fusion process. Focuses on Mathematical Tools That Use Data Fusion This text explores the use of statistical/probabilistic signal/image processing, filtering, component analysis, image algebra, decision making, and neuro-FL–GA paradigms in studying, developing and validating data fusion processes (DFP). It covers major mathematical expressions, and formulae and equations as well as, where feasible, their derivations. It also discusses SDF concepts, DF models and architectures, aspects and methods of type 1 and 2 fuzzy logics, and related practical applications. In addition, the author covers soft computing paradigms that are finding increasing applications in multisensory DF approaches and applications. This book: Explores the use of interval type 2 fuzzy logic and ANFIS in DF Covers the mathematical treatment of many types of filtering algorithms, target-tracking methods, and kinematic DF methods Presents single and multi-sensor tracking and fusion mathematics Considers specific DF architectures in the context of decentralized systems Discusses information filtering, Bayesian approaches, several DF rules, image algebra and image fusion, decision fusion, and wireless sensor network (WSN) multimodality fusion Data Fusion Mathematics: Theory and Practice incorporates concepts, processes, methods, and approaches in data fusion that can help you with integrating DF mathematics and achieving higher levels of fusion activity, and clarity of performance. This text is geared toward researchers, scientists, teachers and practicing engineers interested and working in the multisensor data fusion area.

Handbook Of Multisensor Data Fusion

Author : Martin Liggins II
ISBN : 9781351835374
Genre : Technology & Engineering
File Size : 59. 88 MB
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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.

Data Fusion Concepts And Ideas

Author : H B Mitchell
ISBN : 9783642272226
Genre : Technology & Engineering
File Size : 77. 70 MB
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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 now appear 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 statistical framework. 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.

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