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Mathematical Techniques in Multisensor Data Fusion, Second Edition
David L. Hall and Sonya A.H. McMullen
ISBN 978-1-58053-335-5
Copyright 2004
Pages: 466
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Since the publication of the first edition of this groundbreaking 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.

Besides aiding you in selecting the appropriate algorithm for implementing a 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 defense systems.

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Artech House is pleased to offer you this title in a special In-Print-Forever® (IPF®) hardbound edition. This book is not available from inventory but can be printed at your request and delivered within 2–4 weeks of receipt of order. Please note that because IPF® books are printed on demand, returns cannot be accepted.
"With this second edition, the authors have been successful in updating us with state-of-the-art methods and techniques in multisensor data fusion. Hall and McMullen are well known experts in the field, and should be congratulated for accomplishing such an excellent job in summarizing the up-to-date essential ideas and results on multisensor fusion. Overall, the book is very informative and not difficult to read for electrical and computer engineers as well as technical managers. These types of practitioners can gain solid advice from the book regarding selection of data fusion methods, balance of trade-offs among commercial off-the-shelf tools, development of multisensor data fusion systems and their applications to solve real-world problems. As an engineer in biomedical imaging, I would like to underline the relevance of this book to research on systems biomedicine. The data fusion techniques discussed in this book are closely related to that for biomedical image registration/fusion. Major challenges and new opportunities are enormous ahead of us. In that context, I hope this book will have a significant impact on the biomedical imaging areas, and recommend it to biomedical imaging researchers in particular and other interested engineers in general.”
---BioMedical Engineering OnLine, March 2005

Introduction to Multisensor Data Fusion - Introduction, Fusion Applications, Sensors and Sensor Data, The Inference Hierarchy, A Data Fusion Model, Benefits of Data Fusion, Architectural Concepts and Issues. Limitation of Data Fusion, References

Taxonomy of Algorithms and JDL Model - Taxonomy Overview, Positional Fusion Algorithms, Identity Fusion Algorithms, Ancillary Support Algorithms, References

Level 1: Data Association and Correlation - Process Model for Correlation, Hypothesis Generation, Hypothesis Evaluation, Hypothesis Selection Techniques, References

Level 1: Kinematic and Attribute Estimation - Introduction, Overview of Estimation Techniques, Batch Estimation, Sequential Estimation, Covariance Error Estimation, References

Level 1: Identity Declaration - Identity Declaration and Pattern Recognition, Feature Extraction, Parametric Templates, Cluster Analysis Techniques, Adaptive Neural Networks, Physical Models, Knowledge-Based Methods, Hybrid Methods, References

Level 1: Decision-Level Identity Fusion - Introduction, Classical Inference, Bayesian Inference, Dempster-Shafer’s Method, Generalized Evidence Processing Theory, Heuristic Methods, Implementation and Tradeoffs, References

Levels 2 and 3: Knowledge-Based Approaches - Introduction to Artificial Intelligence, Overview of Expert Systems, Bayesian Belief Nets, Intelligent Agent Systems, Implementation of Expert Systems, Logical Templating Techniques, References

Level 4: Process Monitoring and Optimization - Introduction, Extending the Concept of Level 4 Processing, Techniques for Level 4 Processing, Auction-based Methods, and References

Level 5: Human Computer Interaction - Introduction, Cognitive Aspects of Situation Assessment, Individual Differences in Information Processing, Enabling HCI Technologies, Computer-Aided Situation Assessment, An SBIR Experiment, References

Implementing Data Fusion Systems - Introduction, Requirements Derivation, Sensor Selection and Evaluation, Function Allocation and Decomposition, Architecture Definition, Algorithm Selection, Data Base Definition, HCI Design, Test and Evaluation, References

Emerging Applications - Introduction, Military Applications; Emerging Nonmilitary Applications; COTS Software Survey, Perspectives and Comments, References

TRIP Model - Background, Introduction, TRIP Model, Process Control, Functional Analyses using the TRIP Model, Application of the TRIP Model to the Information Production Process, Summary, References

Automated Information Management - Introduction, Initial Automated Information Manager, Automated Targeting Data Fusion: Structure and Flow, References

Index

David L. Hall is the associate dean for research and graduate programs at The Pennsylvania State University, School of Information Sciences and Technology. He is also the author of Lectures in Multisensor Data Fusion and Target Tracking (Artech House, 2001). He earned his M.S. in Astronomy at The Pennsylvania State University.

is a Captain with the US Air Force. She earned an M.S. in aerospace engineering at Embry-Riddle Aeronautic University.