Advertisement

Two-Phase Identification Algorithm Based on Fuzzy Set and Voting for Intelligent Multi-sensor Data Fusion

  • Sukhoon Kang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4252)

Abstract

Multi-sensor data fusion techniques combine data from multiple sensors in order to get more accurate and efficient meaningful information through several intelligent process levels that may not be possible from a single sensor alone. One of the most important parts in the intelligent data fusion system is the identification fusion, and it can be categorized into physical models, parametric classification and cognitive-based models. In this paper, we present a novel identification fusion method by integrating two fusion approaches such as the parametric classification techniques and the cognitive-based models for achieving high intelligent decision support. We also have confirmed that the reliability and performance of two-phase identification algorithm never fall behind other fusion methods. We thus argue that our heuristics are required for effective decision making in real time for intelligent military situation assessment.

Keywords

Data Fusion Fusion Method Fusion Approach Vote Method Threat Assessment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hall, D.L., Linas, J.: An Introduction to Multisensor Data Fusion. Proceeding of the IEEE 85(1) (1997)Google Scholar
  2. 2.
    Waltz, E., Linas, J.: Multisensor Data Fusion. Artech House, Massachusetts (1990)Google Scholar
  3. 3.
    Zadeh, L.A.: Fuzzy Sets and Systems. North-Holland Press, Amsterdam (1978)Google Scholar
  4. 4.
    Wiley, R.G.: Electronic Intelligence. Arthech House, Massachusetts (1982)Google Scholar
  5. 5.
    Hall, D.L.: Mathematical Techniques in Multisensor Data Fusion. Artech House, Norwood (1992)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sukhoon Kang
    • 1
  1. 1.Department of Computer EngineeringDaejeon UniversityDaejeonKorea

Personalised recommendations