• DocumentCode
    1482638
  • Title

    Subset selection procedures to identify electromagnetic fields following lognormal distributions

  • Author

    Buzaianu, E.M. ; Chen, Peng ; Wu, T.-J.

  • Author_Institution
    Dept. of Math. & Stat., Univ. of North Florida, Jacksonville, FL, USA
  • Volume
    5
  • Issue
    4
  • fYear
    2011
  • fDate
    4/1/2011 12:00:00 AM
  • Firstpage
    458
  • Lastpage
    465
  • Abstract
    The authors use statistical ranking and selection methodology to identify multiple targets in electromagnetic (EM) fields. Previous research concluded that the observed EM field power fluxes and cable powers follow either a chi-square distribution with two degrees of freedom or a lognormal distribution. That is, such an EM field can be characterised by either an exponential distribution with mean μ or a lognormal distribution with parameters μ and μ. Here, the authors propose subset selection procedures to identify EM fields which follow lognormal distributions with common μ, assuming at least one candidate EM field whose parameter μ satisfies the selection criterion. The authors illustrate the properties of our proposed procedures by numerical and simulation examples. Although the research was motivated by assessing electromagnetic vulnerability, the statistical methods that were developed in this article are as general as many other mathematical tools used in electromagnetic fields. The proposed procedures can be applied to any electronic system in radar, sonar and navigation that generate electromagnetic interference.
  • Keywords
    electromagnetic fields; electromagnetic interference; exponential distribution; log normal distribution; EM field power flux; cable power; electromagnetic field; electromagnetic interference; electromagnetic vulnerability; exponential distribution; lognormal distribution; subset selection procedure;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar & Navigation, IET
  • Publisher
    iet
  • ISSN
    1751-8784
  • Type

    jour

  • DOI
    10.1049/iet-rsn.2010.0195
  • Filename
    5739667