Multiple targets characterization of electromagnetic vulnerability

Pinyuen Chen, Lisa Osadciw, Tiee Jian Wu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


We use statistical selection methodology to characterize multiple targets in electromagnetic fields, which result from ground, weather, and sea clutter or internal electromagnetic interference due to the antenna subsystems. This electromagnetic interference occurs at the same frequencies as the target returns yet a specific statistical distribution in amplitude emerges over time. Holland and St. John [Statistical electromagnetics, Technical Report AFRL-DE-PS-TR-1998-1025, Air Force Research Laboratory, Direct Energy Directorate, Air Force Material Command, Kirtland Air Force Base, 1988] concluded that the observed EM field power fluxes and cable powers follow either a chi-square distribution or a log-normal distribution, which implies either distribution in all measurements due to internal electromagnetic interference (EMI) problems. That is such an EM field can be characterized by either an exponential distribution or a log-normal distribution. These cases exist also in a far field as a result of what the aircraft returns, while the distribution exists due to multiple reflecting surfaces instead of internal EM fields from radar subsystems previously mentioned. Clutter also produces these same distributions in the far field. For the exponential distribution case, we propose subset selection procedure to identify EM fields whose reference parameters are those of candidate targets rather than the interfering EM sources. We discuss the properties of our proposed procedure by numerical examples and give simulation examples to illustrate the procedure.

Original languageEnglish (US)
Pages (from-to)344-351
Number of pages8
JournalSignal Processing
Issue number1
StatePublished - Jan 2010


  • Correct selection
  • Electromagnetic field
  • Exponential distribution
  • Log-normal distribution
  • Subset selection

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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