bullet Advances and Challenges in Multisensor Data and Information Processing



  Title: Advances and Challenges in Multisensor Data and Information Processing

  Editor: E. Lefebvre

  Publisher: IOS Press

  Hardcove: 412 pages

  Pubdate: 15 April 2007

  ISBN: 1586037277



 Book's cover

Book Description



Information fusion resulting from multi-source processing, often called multisensor data fusion when sensors are the main sources of information, is a relatively young (less than 20 years) technology domain. It provides techniques and methods for: Integrating data from multiple sources and using the complementarity of this data to derive maximum information about the phenomenon being observed; Analyzing and deriving the meaning of these observations; Selecting the best course of action; and Controlling the actions. Various sensors have been designed to detect some specific phenomena, but not others. Data fusion applications can combine synergically information from many sensors, including data provided by satellites and contextual and encyclopedic knowledge, to provide enhanced ability to detect and recognize anomalies in the environment, compared with conventional means. Data fusion is an integral part of multisensor processing, but it can also be applied to fuse non-sensor information (geopolitical, intelligence, etc.) to provide decision support for a timely and effective situation and threat assessment. One special field of application for data fusion is satellite imagery, which can provide extensive information over a wide area of the electromagnetic spectrum using several types of sensors (Visible, Infra-Red (IR), Thermal IR, Radar, Synthetic Aperture Radar (SAR), Polarimetric SAR (PolSAR), Hyperspectral...). Satellite imagery provides the coverage rate needed to identify and monitor human activities from agricultural practices (land use, crop types identification...) to defense-related surveillance (land/sea target detection and classification). By acquiring remotely sensed imagery over earth regions that land sensors cannot access, valuable information can be gathered for the defense against terrorism.


This book deals with the following research areas: Target recognition/classification and tracking; Sensor systems; Image processing; Remote sensing and remote control; Belief functions theory; and Situation assessment.


First Ten Chapters:

  1. Sensor Data Fusion: Methods, Applications, Examples /W. Koch

  2. Simulation of Distributed Sensor Networks /K. Alexiev

  3. Joint Target Tracking and Classification via Sequential Monte Carlo Filtering /D. Angelova and L. Mihaylova

  4. A Survey on Assignment Techniques /F. Opitz

  5. Non-Linear Techniques in Target Tracking /T. Kausch, K. Dästner and F. Opitz

  6. Underwater Threat Source Localization: Processing Sensor Network TDOAs with a Terascale Optical Core Device /J. Barhen, N. Imam, M. Vose, A. Averbuch and M. Wardlaw

  7. On Quality of Information in Multi-Source Fusion Environments /E. Lefebvre, M. Hadzagic and É. Bossé

  8. Polarimetric Features and Contextual Information Fusion for Automatic Target Detection and Recognition /Y. Allard, M. Germain and O. Bonneau

  9. Enhancing Efficiency of Dynamic Threat Analysis for Combating and Competing Systems / E. Pogossian, A. Javadyan and E. Ivanyan

  10. Evidence Theory for Robust Ship Identification in Airborne Maritime Surveillance Missions / P. Valin



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