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Multisensor Data Fusion (Electrical Engineering & Applied Signal Processing Series) [Hardcover]

David L. Hall (Editor), James Llinas (Editor)
4.3 out of 5 stars  See all reviews (3 customer reviews)


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Book Description

0849323797 978-0849323799 June 20, 2001 1
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.


  • Product Details

    • Hardcover: 568 pages
    • Publisher: CRC Press; 1 edition (June 20, 2001)
    • Language: English
    • ISBN-10: 0849323797
    • ISBN-13: 978-0849323799
    • Product Dimensions: 10.1 x 6.6 x 1.4 inches
    • Shipping Weight: 2.5 pounds
    • Average Customer Review: 4.3 out of 5 stars  See all reviews (3 customer reviews)
    • Amazon Best Sellers Rank: #2,200,578 in Books (See Top 100 in Books)

     

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    5 of 7 people found the following review helpful:
    5.0 out of 5 stars This Book is the Authorative Handbook - Highly Recommended!!, February 2, 2004
    By 
    T. Bass "Tim Bass" (Palo Alto, CA United States) - See all my reviews
    (REAL NAME)   
    This review is from: Multisensor Data Fusion (Electrical Engineering & Applied Signal Processing Series) (Hardcover)
    Related quotes from Bass, T., Intrusion Detection Systems & Multisensor Data Fusion, Communications of the ACM, pp. 99-105, Vol. 43, No. 4, April 2000:

    Multisensor data fusion or distributed sensing, is a relatively new engineering discipline used to combine data from multiple and diverse sensors and sources in order to make inferences about events, activities, and situations. These systems are often compared to the human cognitive process where the brain fuses sensory information from the various sensory organs, evaluates situations, makes decisions, and directs action.

    Data fusion technology has been applied most prominently to military applications such as battlefield surveillance and tactical situation assessment. Data fusion has also emerged in commercial applications such as robotics, manufacturing, medical diagnosis, and remote sensing.

    The application of data fusion in technical systems requires mathematical and heuristic techniques from fields such as statistics, artificial intelligence, operations research, digital signal processing, pattern recognition, cognitive psychology, information theory and decision theory.

    In a typical military command and control (C2) system, data fusion sensors are used to observe electromagnetic radiation, acoustic and thermal energy, nuclear particles, infrared radiation, noise and other signals. Multisensor data fusion provides an important functional framework for building next generation information fusion and cyberspace situational awareness systems.

    There exist significant opportunities and numerous technical challenges for the commercial application of data fusion theory into the art and science of modern decision support systems. This handbook provides the absolute best possible overview of the art and science of multisensor data fusion technology.

    Congratulations to David Hall and James Llinas for great editorial work on this handbook. I strongly recommend this book to anyone working in this wonderful and rapidly evolving field.

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    5.0 out of 5 stars MUST have, January 9, 2010
    Amazon Verified Purchase(What's this?)
    This review is from: Multisensor Data Fusion (Electrical Engineering & Applied Signal Processing Series) (Hardcover)
    If you're interested or are in the information fusion field - YOU MUST HAVE THIS BOOK!!!
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    0 of 25 people found the following review helpful:
    3.0 out of 5 stars MotownBlue, August 3, 2005
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    This review is from: Multisensor Data Fusion (Electrical Engineering & Applied Signal Processing Series) (Hardcover)
    Useful overview for users of Oracle's Java IDE. Most useful for n-tier development with Oracle's database & application server. Not as useful for 2 tier or desktop developers.
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    Inside This Book (learn more)
    First Sentence:
    Integration or fusion of data from multiple sensors improves the accuracy of applications ranging from target tracking and battlefield surveillance to nondefense applications such as industrial process monitoring and medical diagnosis. Read the first page
    Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
    fusion process model, unified tracking, data fusion activities, decentralized data fusion, spatial data fusion, fusion tree paradigm, data fusion systems, data association hypothesis, situation awareness development, multidimensional assignment problem, developing predictive diagnostics, joint multitarget probabilities, tracking recursion, true conditioning event, image data fusion, multitarget likelihood, target state space, data fusion automation, data fusion levels, database design criteria, data association decisions, nonlinear filtering equations, spatial object hierarchy, covariance intersection, data fusion community
    Key Phrases - Capitalized Phrases (CAPs): (learn more)
    Handbook of Multisensor Data Fusion, Artech House, New York, Air Force, Penn State, Academic Press, John Wiley, Monte Carlo, Automatic Control, Applied Physics Laboratory, Johns Hopkins University, Contrasting Approaches, Multitarget-Multisensor Tracking, Radar Applications, University of Oxford, Intelligent Systems, Naval Research Laboratory, Sensor Symp, Case Study, Prentice Hall, San Diego, Technology Magazine, The Bayesian Iceberg, Virginia Beach, Cambridge University Press
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