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Book Description

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.

Table of Contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Contents
  7. Preface
  8. Acknowledgment
  9. Editors
  10. Contributors
  11. 1 Multisensor Data Fusion
  12. 2 Data Fusion Perspectives and Its Role in Information Processing
  13. 3 Revisions to the JDL Data Fusion Model
  14. 4 Introduction to the Algorithmics of Data Association in Multiple-Target Tracking
  15. 5 Principles and Practice of Image and Spatial Data Fusion
  16. 6 Data Registration
  17. 7 Data Fusion Automation: A Top-Down Perspective
  18. 8 Overview of Distributed Decision Fusion
  19. 9 Introduction to Particle Filtering: The Next Stage in Tracking
  20. 10 Target Tracking Using Probabilistic Data Association-Based Techniques with Applications to Sonar, Radar, and EO Sensors
  21. 11 Introduction to the Combinatorics of Optimal and Approximate Data Association
  22. 12 Bayesian Approach to Multiple-Target Tracking
  23. 13 Data Association Using Multiple-Frame Assignments
  24. 14 General Decentralized Data Fusion with Covariance Intersection
  25. 15 Data Fusion in Nonlinear Systems
  26. 16 Random Set Theory for Multisource-Multitarget Information Fusion
  27. 17 Distributed Fusion Architectures, Algorithms, and Performance within a Network-Centric Architecture
  28. 18 Foundations of Situation and Threat Assessment
  29. 19 Introduction to Level 5 Fusion: The Role of the User
  30. 20 Perspectives on the Human Side of Data Fusion: Prospects for Improved Effectiveness Using Advanced Human–Computer Interfaces
  31. 21 Requirements Derivation for Data Fusion Systems
  32. 22 Systems Engineering Approach for Implementing Data Fusion Systems
  33. 23 Studies and Analyses within Project Correlation: An In-Depth Assessment of Correlation Problems and Solution Techniques
  34. 24 Data Management Support to Tactical Data Fusion
  35. 25 Assessing the Performance of Multisensor Fusion Processes
  36. 26 Survey of COTS Software for Multisensor Data Fusion
  37. 27 Survey of Multisensor Data Fusion Systems
  38. 28 Data Fusion for Developing Predictive Diagnostics for Electromechanical Systems
  39. 29 Adapting Data Fusion to Chemical and Biological Sensors
  40. 30 Fusion of Ground and Satellite Data via Army Battle Command System
  41. 31 Developing Information Fusion Methods for Combat Identification
  42. Index
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