• DocumentCode
    875427
  • Title

    "Statistics 101" for multisensor, multitarget data fusion

  • Author

    Mahler, Ronald P S

  • Author_Institution
    Lockheed Martin NE&SS Tactical Syst., Eagan, MN, USA
  • Volume
    19
  • Issue
    1
  • fYear
    2004
  • Firstpage
    53
  • Lastpage
    64
  • Abstract
    This tutorial summarizes the motivations, concepts, techniques, and applications of finite-set statistics (FISST), a system-level, "top-down" direct generalization of ordinary single-sensor, single-target engineering statistics to the multisensor, multitarget realm. FISST provides powerful new conceptual and computational methods for dealing with multisensor, multitarget, and multi-evidence data fusion problems. The paper begins with a broad-brush overview of the basic concepts of FISST. It describes how conventional single-sensor, single-target formal Bayesian modeling is carefully extended to general data fusion problems. We examine a simple example: joint detection and tracking of a possibly non-existent maneuvering target in heavy clutter. The tutorial concludes with a commentary on certain criticisms of FISST.
  • Keywords
    Bayes methods; probability; radar clutter; sensor fusion; target tracking; tracking filters; Statistics 101 concepts; finite-set statistics; formal Bayesian modeling; heavy clutter; joint detection and tracking; multievidence data fusion; multisensor multitarget data fusion; possibly nonexistent maneuvering target; system-level top-down direct generalization; tutorial; Algorithm design and analysis; Bayesian methods; Data engineering; Power engineering and energy; Power engineering computing; Reliability engineering; Signal processing; Signal processing algorithms; Statistics; Target tracking;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    0885-8985
  • Type

    jour

  • DOI
    10.1109/MAES.2004.1263231
  • Filename
    1263231