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Description

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:

  • offers a thorough introduction to data fusion terminology and models

  • describes advanced techniques for data association, target tracking, and identification

  • presents practical information on system development, including requirements analysis, systems engineering, algorithm selection, database design, human-computer interfaces, and performance assessment

  • introduces applications from the DoD, NASA, DARPA, and condition-based monitoring of complex machinery

  • supplies data fusion resources and Web sites

    The 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.

  • 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

    Name: Multisensor Data Fusion (eBook)CRC Press 
    Description: Edited by David Hall, James LlinasSeries Editor: Richard C. Dorf, Alexander D. PoularikasContributors: Simon Julier, Aubrey Poore, R. R. Brooks, Christopher Bowman, Yaakov Bar-Shalom, Lawrence Stone, Ronald P. Mahler, T. Kirubarajan, Joe W. Carl, Alan N. Steinberg, Carl Byington, Ed Waltz, Jeffrey Uhlmann, Robert J. Hansen, Mary Jane Hall, Suihua Lu, Brian Suchomel, Richard Anthony, Amulya Garga, Steven Zornetzer, Kenneth Ford, Daniel Cooke, Lynne Grewe, S.A. Hall, T. Tate, Hans Keithley, Mary L. Nichols, Shikha Miglani. 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...
    Categories: Digital Signal Processing