About the Book
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:ooffers a thorough introduction to data fusion terminology and modelsodescribes advanced techniques for data association, target tracking, and identificationopresents practical information on system development, including requirements analysis, systems engineering, algorithm selection, database design, human-computer interfaces, and performance assessmentointroduces applications from the DoD, NASA, DARPA, and condition-based monitoring of complex machineryosupplies data fusion resources and Web sitesThe 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.
Table of Contents:
MULTISENSOR DATA FUSION
Introduction to Multisensor Data Fusion, D. Hall and J. Llinas
The JDL Data Fusion Process Model, A. Steinberg and C. Bowman
Introduction to the Algorithms of Data Association in Multiple-Target Tracking, J.K. Uhlmann
The Principles and Practice of Image and Spatial Data Fusion, E. Waltz
Data Registration, R. Brooks and L. Grewe
Data Fusion Automation: A Top-Down Perspective, R. Antony
Contrasting Approaches to Combine Evidence, J. Carl
ADVANCED TRACKING AND ASSOCIATION METHODS
Target Tracking Using Probabilistic Data Association-Based Techniques and Applications to Sonar, Radar, and EO Sensors, T. Kirubarajan and Y. Bar-Shalom
An Introduction to the Combinatorics of Optimal and Approximate Data Association, J.K. Uhlmann
A Bayesian Approach to Multiple-Target Tracking, L. Stone
Data Association Using Multiple Frame Assignments, A. Poore, S. Lu, and B.J. Suchomel
General Decentralized Data Fusion with Covariance Intersection, S. Julier and J. Uhlmann
Data Fusion in Non-Linear Systems, S. Julier and J. Uhlmann
Random Set Theory for Target Tracking and Identification, R. Mahler
SYSTEMS ENGINEERING AND IMPLEMENTATION
Requirements Derivation for Data Fusion Systems, E. Waltz and D. Hall
A Systems Engineering Approach for Implementing Data Fusion Systems, C. Bowman and A. Steinberg
Studies and Analyses with Project Correlation: An In-Depth Assessment of Correlation Problems and Solution Techniques, J. Llinas, L. McConnell, C. Bowman, D. Hall, and P. Applegate
Data Management Support to Tactical Data Fusion, R. Antony
Removing the HCI Bottleneck: How the Human-Computer Interface (HCI) Affects the Performance of Data Fusion Systems, M.J. Hall, S.A. Hall, and T. Tate
Assessing the Performance of Multisensor Fusion Processes, J. Llinas
Dirty Secrets in Data Fusion, D. Hall and A. Steinberg
SAMPLE APPLICATIONS
A Survey of Multisensor Data Fusion Systems, M. Nichols
Data Fusion for Developing Predictive Diagnostics for Electromechanical Systems, C. Byington and A. Garga
Information Technology for NASA in the 21st Century, R.J. Hansen, D. Cooke, K. Ford, and S. Zornetzer
Data Fusion for a Distributed Ground-Based Sensing System, R. Brooks
An Evaluation Methodology for Fusion Processes Based on Information Needs, H. Keithley
RESOURCES
Web Sites Related to Multi-Sensor Data Fusion
Index
