Copula based dependence modeling for inference in RADAR systems

Sora Choi, Hao He, Pramod K. Varshney

Research output: Chapter in Book/Entry/PoemConference contribution


Statistical dependence is one of the significant design issues in various radar systems for inference tasks including detecting an activity of interest or estimating states or parameters for situational awareness. Modeling dependence has been discussed in many articles on radar and the research has shown that taking dependence into account improves performance of inference tasks. In this paper, we introduce copulas as flexible tools for modeling of nonlinear/linear dependence. Copulas allow one to model the dependence structures among random variables with arbitrary marginal distributions. We explore the potential use of copula theory in radar systems while discussing the dependence modeling problem. Then we present an application for binary hypothesis testing to show the benefit of using copula theory.

Original languageEnglish (US)
Title of host publication2015 IEEE Radar Conference - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781467396554
StatePublished - 2015
EventIEEE Radar Conference - Johannesburg, South Africa
Duration: Oct 27 2015Oct 30 2015

Publication series

Name2015 IEEE Radar Conference - Proceedings


OtherIEEE Radar Conference
Country/TerritorySouth Africa

ASJC Scopus subject areas

  • Signal Processing
  • Instrumentation


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