Copula based dependence modeling for inference in RADAR systems

Sora Choi, Hao He, Pramod Kumar Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.
Pages197-202
Number of pages6
ISBN (Electronic)9781467396554
DOIs
StatePublished - Feb 17 2015
EventIEEE Radar Conference - Johannesburg, South Africa
Duration: Oct 27 2015Oct 30 2015

Other

OtherIEEE Radar Conference
CountrySouth Africa
CityJohannesburg
Period10/27/1510/30/15

ASJC Scopus subject areas

  • Signal Processing
  • Instrumentation

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    Choi, S., He, H., & Varshney, P. K. (2015). Copula based dependence modeling for inference in RADAR systems. In 2015 IEEE Radar Conference - Proceedings (pp. 197-202). [7411879] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RadarConf.2015.7411879