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Distributed Detection And Data Fusion
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Book Synopsis Distributed Detection and Data Fusion by : Pramod K. Varshney
Download or read book Distributed Detection and Data Fusion written by Pramod K. Varshney and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introductory treatment of the fundamentals of decision-making in a distributed framework. Classical detection theory assumes that complete observations are available at a central processor for decision-making. More recently, many applications have been identified in which observations are processed in a distributed manner and decisions are made at the distributed processors, or processed data (compressed observations) are conveyed to a fusion center that makes the global decision. Conventional detection theory has been extended so that it can deal with such distributed detection problems. A unified treatment of recent advances in this new branch of statistical decision theory is presented. Distributed detection under different formulations and for a variety of detection network topologies is discussed. This material is not available in any other book and has appeared relatively recently in technical journals. The level of presentation is such that the hook can be used as a graduate-level textbook. Numerous examples are presented throughout the book. It is assumed that the reader has been exposed to detection theory. The book will also serve as a useful reference for practicing engineers and researchers. I have actively pursued research on distributed detection and data fusion over the last decade, which ultimately interested me in writing this book. Many individuals have played a key role in the completion of this book.
Book Synopsis Distributed Data Fusion for Network-Centric Operations by : David Hall
Download or read book Distributed Data Fusion for Network-Centric Operations written by David Hall and published by CRC Press. This book was released on 2017-12-19 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the recent proliferation of service-oriented architectures (SOA), cloud computing technologies, and distributed-interconnected systems, distributed fusion is taking on a larger role in a variety of applications—from environmental monitoring and crisis management to intelligent buildings and defense. Drawing on the work of leading experts around the world, Distributed Data Fusion for Network-Centric Operations examines the state of the art of data fusion in a distributed sensing, communications, and computing environment. Get Insight into Designing and Implementing Data Fusion in a Distributed Network Addressing the entirety of information fusion, the contributors cover everything from signal and image processing, through estimation, to situation awareness. In particular, the work offers a timely look at the issues and solutions involving fusion within a distributed network enterprise. These include critical design problems, such as how to maintain a pedigree of agents or nodes that receive information, provide their contribution to the dataset, and pass to other network components. The book also tackles dynamic data sharing within a network-centric enterprise, distributed fusion effects on state estimation, graph-theoretic methods to optimize fusion performance, human engineering factors, and computer ontologies for higher levels of situation assessment. A comprehensive introduction to this emerging field and its challenges, the book explores how data fusion can be used within grid, distributed, and cloud computing architectures. Bringing together both theoretical and applied research perspectives, this is a valuable reference for fusion researchers and practitioners. It offers guidance and insight for those working on the complex issues of designing and implementing distributed, decentralized information fusion.
Book Synopsis New Results in Distributed Detection and Data Fusion for Target Tracking by : Constantino Rago
Download or read book New Results in Distributed Detection and Data Fusion for Target Tracking written by Constantino Rago and published by . This book was released on 1995 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Distributed Detection Using a Data Fusion Center with 2-bit Memory by : Huang-Hsiao Kao
Download or read book Distributed Detection Using a Data Fusion Center with 2-bit Memory written by Huang-Hsiao Kao and published by . This book was released on 1995 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Fusion for Adaptive Distributed Detection by : Ari Naim
Download or read book Data Fusion for Adaptive Distributed Detection written by Ari Naim and published by . This book was released on 1989 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multisensor Data Fusion by : Hassen Fourati
Download or read book Multisensor Data Fusion written by Hassen Fourati and published by CRC Press. This book was released on 2017-12-19 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Fusion for Situation Monitoring, Incident Detection, Alert and Response Management by : E. Shahbazian
Download or read book Data Fusion for Situation Monitoring, Incident Detection, Alert and Response Management written by E. Shahbazian and published by IOS Press. This book was released on 2006-03-02 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Fusion is a very broad interdisciplinary technology domain. It provides techniques and methods for; integrating information from multiple sources and using the complementarities of these detections to derive maximum information about the phenomenon being observed; analyzing and deriving the meaning of these observations and predicting possible consequences of the observed state of the environment; selecting the best course of action; and controlling the actions. Here, the focus is on the more mature phase of data fusion, namely the detection and identification / classification of phenomena being observed and exploitation of the related methods for Security-Related Civil Science and Technology (SST) applications. It is necessary to; expand on the data fusion methodology pertinent to Situation Monitoring, Incident Detection, Alert and Response Management; discuss some related Cognitive Engineering and visualization issues; provide an insight into the architectures and methodologies for building a data fusion system; discuss fusion approaches to image exploitation with emphasis on security applications; discuss novel distributed tracking approaches as a necessary step of situation monitoring and incident detection; and provide examples of real situations, in which data fusion can enhance incident detection, prevention and response capability. In order to give a logical presentation of the data fusion material, first the general concepts are highlighted (Fusion Methodology, Human Computer Interactions and Systems and Architectures), closing with several applications (Data Fusion for Imagery, Tracking and Sensor Fusion and Applications and Opportunities for Fusion).
Book Synopsis Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks by : Ahmed Abdelgawad
Download or read book Resource-Aware Data Fusion Algorithms for Wireless Sensor Networks written by Ahmed Abdelgawad and published by Springer Science & Business Media. This book was released on 2012-02-15 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative. Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.
Book Synopsis Handbook of Multisensor Data Fusion by : Martin Liggins II
Download or read book Handbook of Multisensor Data Fusion written by Martin Liggins II and published by CRC Press. This book was released on 2017-01-06 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Fusion in Wireless Sensor Networks by : Domenico Ciuonzo
Download or read book Data Fusion in Wireless Sensor Networks written by Domenico Ciuonzo and published by Control, Robotics and Sensors. This book was released on 2019-05-03 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the advanced tools required to design state-of-the-art inference algorithms for inference in wireless sensor networks. Written for the signal processing, communications, sensors and information fusion research communities, it covers the emerging area of data fusion in wireless sensor networks.
Book Synopsis Information Fusion in Distributed Sensor Networks with Byzantines by : Andrea Abrardo
Download or read book Information Fusion in Distributed Sensor Networks with Byzantines written by Andrea Abrardo and published by Springer Nature. This book was released on 2020-07-14 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the most powerful attack strategies and potential defense mechanisms, always approaching the interplay between the Fusion Center and the Byzantines from a game-theoretic perspective. For each of the settings considered, the equilibria of the game and the corresponding payoffs are derived, shedding new light on the achievable performance level and the impact that the presence of the Byzantines has on the accuracy of decisions made by the Fusion Center. Accordingly, the book offers a simple yet effective introduction to the emerging field of adversarial information fusion, providing a wealth of intuitive take-home lessons for practitioners interested in applying the most basic notions to the design of practical systems, while at the same time introducing researchers and other readers to the mathematical details behind the theory.
Book Synopsis Distributed Detection Theory and Data Fusion by :
Download or read book Distributed Detection Theory and Data Fusion written by and published by . This book was released on 1999 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report presents a summary of research results obtained during the course of this grant in the area of distributed signal detection and decision fusion. Specifically, distributed detection and estimation with fuzzy information, intelligent CFAR detection, computational algorithms for system design and BDT based signal classification were considered. A brief discussion of these results is provided here. For more details, the reader is referred to the list of published papers.
Book Synopsis A Theory for Distributed Signal Detection and Data Fusion by :
Download or read book A Theory for Distributed Signal Detection and Data Fusion written by and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research attempts to develop a fundamental understanding of the issues involved in the design and performance analysis of distributed detection schemes. Such knowledge is currently lacking. This is especially true for cases with statistically dependent observations from sensor to sensor, a practical case on which this research focuses. Some emphasis is being devoted to developing design algorithms and on applications. The goal of these studies is to produce tools and techniques for pressing practical problems. We classify our efforts into four basic areas: properties of dependent observations cases, design algorithms, applications and image fusion.
Book Synopsis Multisensor Data Fusion by : David Hall
Download or read book Multisensor Data Fusion written by David Hall and published by CRC Press. This book was released on 2001-06-20 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 evolut
Book Synopsis Optimization of Distributed Detection Systems in the Presence of Wireless Channel Uncertainty by : Hamidreza Ahmadi
Download or read book Optimization of Distributed Detection Systems in the Presence of Wireless Channel Uncertainty written by Hamidreza Ahmadi and published by . This book was released on 2013 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: "We study data fusion in a distributed detection system, consisting of several geographically dispersed signal detectors and a fusion center (FC), that is tasked with solving an underlying binary hypothesis testing problem (e.g., detection of a signal source or a target in a field being monitored). Each detector makes a binary local decision based on its local observation, where each local decision has a certain reliability index, determined by the observation quality. These local decisions are digitally modulated and transmitted over wireless channels to neighboring detectors and/or the FC. The FC is tasked with fusing the data received from the detectors and making a global binary decision. The challenge in data fusion is that the binary local decisions would be corrupted due to wireless channel effects (i.e., additive Gaussian noise and multipath fading). These effects further limit the reliability of the global decision. This raises a key question: Aiming to maximize the reliability of the global decision, what is the optimal distributed detection system design in the presence of wireless channel uncertainty? To address this question in this thesis, we identify and address three subproblems as the following: P1) Suppose the topology (i.e., the wireless connections between the local detectors and the FC that are used for transmission of local binary decisions) of the distributed detection system is adaptive and can be selected based on the observation and communication channel qualities. What are the best network topology and the best signal processing schemes (i.e., local decision rules and data fusion rules)? How are the best topology and the best signal processing schemes related to the reliability indices of the local decisions, channel noise and fading? Our results indicate that the optimality of widely used parallel topology, in which the local detectors directly communicate with the FC, is limited. We also demonstrate the average performance gain of topology adaptation compared with a fixed topology system. P2) Channel estimation is an integral part of most of today's wireless communication systems. Via transmitting known training symbols, the local detectors enable the FC to estimate the unknown fading channel, which is used for recovering data symbols. Considering a distributed detection system with a parallel topology, in which the local detectors transmit training symbols, followed by their local binary decisions, and assuming an average transmit power constraint, we ask: What is the best data fusion rule at the FC? How is this fusion rule affected by channel estimation error, transmit power allocation between training and data symbols, and the communication reception mode at the FC (i.e., coherent versus noncoherent)? Our study shows that with noncoherent reception, the detection performance of the FC is maximized when no training symbol is transmitted and all transmit power is spent for only data symbols. This performance is attainable with statistics-based likelihood-ratio-test (LRT) rule for random channels and generalized LRT (GLRT) for deterministic channels. With coherent reception, however, the optimal power allocation depends on the fading model. For Rayleigh fading model, the total detection probability and error exponent are maximized when half of the transmit power is spent for training symbols. Whereas, for Rician fading model, the optimal power allocation depends on the operating signal-to-noise (SNR) and Rice factor. P3) Suppose the distributed detection system is tasked with detecting a Gaussian signal source, where in its presence, local observations are statistically correlated samples of the signal source, corrupted by an additive Gaussian noise. We ask: What is the best linear data fusion rule at the FC? How is this fusion rule affected by the statistical correlation, the reliability indices of the local decisions, transmit power constraints at the local detectors, communication multiple access scheme (employed by the local detectors to communicate with the FC), the communication reception mode at the FC, channel noise and fading? We show that statistical correlation degrades the detection probability of the system. We also find the optimal power allocation for different communication multiple access schemes, subject to several transmit power constraints, in terms of observation and wireless channel qualities"--Pages v-vi.
Book Synopsis Data Fusion Applications by : S. Pfleger
Download or read book Data Fusion Applications written by S. Pfleger and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data fusion, the ability to combine data derived from several sources to provide a coherent, informative, and useful characterization of a situation,is a challenging task. There is no unified and proven solution which is applicable in all circumstances, but there are many plausible and useful approaches which can be and are used to solve particular applications. This volume presents the proceedings of the workshop Data Fusion Applications hosted in Brussels by the 1992 ESPRIT Conference and Exhibition. It contains 22 papers from 69 experts,who present advanced research results on data fusion together with practicalsolutions to multisensor data fusion in a wide variety of applications: real-time expert systems, robotics, medical diagnosis and patient surveillance, monitoring and control, marine protection, surveillance and safety in public transportation systems, image processing and interpretation, and environmental monitoring. The research forms part of the ESPRIT project DIMUS (Data Integration in Multisensor Systems).
Book Synopsis Data Fusion With Communication Applications by :
Download or read book Data Fusion With Communication Applications written by and published by . This book was released on 2003 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data fusion ideas were employed to solve some important communication system problems. The first topic involves studying methods for generating and combining decisions from individual receivers in a multiple user scenario. The resulting theory of distributed multiuser detection or multiuser decision fusion has applications in both communications and in more classical problems of data fusion. In current digital cellular networks, for example, this theory is useful for combining decisions made at several remote base stations. This project focused on designing algorithms for and analyzing the performance and complexity of such schemes. The approach involved developing the theory for distributed multiuser detection by building on single user distributed detection theory, to which the PI has been a major contributor over the last few years. The second topic involved the study of methods employing multiple transmit and receive antennas (MIMO methods) to enhance performance. We developed new improved space-time codes and gave particular attention to the use of MIMO methods in a system (as opposed to a link which is interference free) which has not received much study.
