Monte-Carlo based estimation methods for rapidly-varying sea clutter

Ying Li, William Moran, Sandeep P. Sira, Antonia Papandreou-Suppappola, Darryl Morrell

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

6 Scopus citations

Abstract

We consider two Monte-Carlo based methods for characterizing the scattering function of rapidly-varying sea clutter. The first method uses multiple particle filtering to estimate the clutter space-time covariance marix by exploiting the structure of the matrix. This method is then compared to a baseline approach that estimates the clutter covariance matrix based on the Weibull distribution approximation. Both methods are evaluated by formulating a detection problem that simulates a small moving target in heavy sea clutter.

Original languageEnglish (US)
Title of host publication2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings
Pages256-261
Number of pages6
DOIs
StatePublished - 2009
Event2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009 - Marco Island, FL, United States
Duration: Jan 4 2009Jan 7 2009

Publication series

Name2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings

Other

Other2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009
Country/TerritoryUnited States
CityMarco Island, FL
Period1/4/091/7/09

Keywords

  • Covariance matrix estimation
  • Monte Carlo simulations
  • Multiple particle filtering
  • Weibull distribution

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Electrical and Electronic Engineering

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