By (author)s: Erik P. Blasch, Dale Lambert

Copyright: 2012
Pages: 376
ISBN: 9781608071524

Our Price: $112.00
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Description
High-level information fusion is the ability of a fusion system to capture awareness and complex relations, reason over past and future events, utilize direct sensing exploitations and tacit reports, and discern the usefulness and intention of results to meet system-level goals. This authoritative book serves a practical reference for developers, designers, and users of data fusion services that must relate the most recent theory to real-world applications. This unique volume provides alternative methods to represent and model various situations and describes design component implementations of fusion systems. Designers find expert guidance in applying current theories, selecting algorithms and software components, and measuring expected performance of high-level fusion systems.
Table Of Contents
Introduction - High-Level Information Fusion (HLIF) Challenges. Book Structure. A Science of High-Level Information Fusion. ; Situation Assessment and Situation Awareness -Introduction. Situation Awareness and Situation Assessment Defined. Situation Awareness (SAW) Models. Situation Assessment Models. Situational Assessment Model Based on Activities of Interest. Current Information Fusion Situation Assessment Reference Model for Information Fusion. Discussion. Conclusions. ; The State Transition Data Fusion Model - Information Revolution. State Transitions. The STDF Fusion Process. Level 0 Fusion. Level 1 Fusion. Level 2 Fusion. Level 3 Fusion. ; Formalization of Situation Analysis Through Interpreted Systems Semantics -Introduction. Background. Formalization of the Situation Analysis Process. Illustrations on a Surveillance Scenario. Conclusions.; The Role of Information Management to Support High-Level Fusion -Introduction: What Is Information Management and Why Do We Care? Model of Information Management. Information Management Challenges in a Coalition Environment. Information Management Best Practices. Information Management Support to Information Fusion. Information Management from an Agent Perspective. Conclusions. ; Coalition Distributed Information Fusion Testbed - Models of Collaboration. Requirements. CoAX (Collaboration 2002 Experiment). Architecture. Conclusion. ; Information Fusion and Resource Management Testbed -Introduction. INFORM Lab architecture. INFORM Lab Implementation. Tests and Validation. Conclusion. ; The Legal Agreement Protocol - Conceptualization. Formalization. Computation. Sample Vignette. ; User-Defined Operating Picture (UDOP) -Introduction. The Need for a New Picturing Capability: UDOP. Characteristics of a UDOP. Realizing a Future UDOP Capability. A Few Examples of Remaining Issues. Conclusions. ; User Information Fusion Decision Making Analysis with the C-OODA Model -Introduction. Decision Making Models. The Cognitive OODA Loop. Simulation. Discussions and Conclusions.; Scenario-Based Design for Situation Analysis -Introduction. Findings on SBD Methodology. Scenario-Based Design Process Based on Atlantis Problem Scenario. Conclusion. ; A Coalition Approach to High-Level Information Fusion -Introduction. Scenario. CDIFT. Platforms, Sensor Models, and Trackers. Fusion 2+. Indicators of Collective Behaviour. STDF Model. Higher COP. Urban Operations. Combat Search and Rescue (CSAR). Conclusion. ; Operating Condition Scenario Modeling for Information Fusion Assessment -Introduction. Operating Condition Model Terminology. Operating Condition Model Design. Example Operating Conditions. Conditioning on Operating Conditions. Conclusions. ; A Toolbox for the Evaluation of Surveillance Strategies Based on Interpreted Systems -Introduction. Situations Generated By Motion And Sensing Strategies. Situation Analysis Toolbox. Conclusions. ; Measuring the Worthiness of Situation Assessment -Introduction. The Situation Assessment Concept. Metrics. Example. Conclusions. ; Measures of Effectiveness for High-Level Information Fusion -Introduction. Background. Information Fusion Quality Measures. Information Fusion MOEs. Situation Awareness Example. Conclusions. ; Summary - Current Trends. Future. ;

Author

  • Erik P. Blasch

    is a program officer at the United States Air Force Research Laboratory (AFRL) Air Force Office of Scientific Research (AFOSR). He received Ph.D. in electrical engineering from Wright State University. He is a Fellow of IEEE.

  • Dale Lambert Dale Lambert is head of Australia's Defence Science Technology Office's initiative into fusion for situation awareness. He holds a Ph.D. in artificial intelligence and a graduate certificate in management.