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Random Sets pp 185-207 | Cite as

Random Sets in Data Fusion Multi-Object State-Estimation as a Foundation of Data Fusion Theory

  • Shozo Mori
Chapter
Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 97)

Abstract

A general class of multi-object state-estimation problems is defined as the problems for estimating random sets based on information given as collections of random sets. A general solution is described in several forms, including the one using the conditional Choquet’s capacity functional. This paper explores the possibility of the abstract formulation of multi-object state-estimation problems becoming a foundation of data fusion theory. Distributed data processing among multiple “intelligent” processing nodes will also be briefly discussed as an important aspect of data fusion theory.

Key words

Data Fusion Distributed Data Processing Multi-Object State-Estimation Multi-Target/Multi-Sensor Target-Tracking 

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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Shozo Mori
    • 1
  1. 1.Texas Instruments, Inc.Advanced C3I SystemsSan JoséUSA

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