2 Scopus citations

Abstract

This paper explores a new and efficient method for estimating the parameters of the compound K-distribution model of sea clutter when the thermal noise power is also unknown. Current methods for the model parameter estimation include the intensity moments approach that assumes knowledge of the thermal noise power and a three-dimensional (3-D) curve fitting approach that is very computationally intensive. The proposed method integrates the intensity moments with a nonlinear one-dimensional (1-D) curve-fitting procedure to also allow for an efficient estimate of the thermal noise power. It is also extended to incorporate fractional moments used under the condition of known clutter-to-noise ratios. The performance of the new approach is demonstrated using both simulated and real sea clutter observations.

Original languageEnglish (US)
Title of host publicationConference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages2091-2095
Number of pages5
ISBN (Electronic)9781538692189
DOIs
StatePublished - Feb 19 2019
Event52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 - Pacific Grove, United States
Duration: Oct 28 2018Oct 31 2018

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2018-October
ISSN (Print)1058-6393

Conference

Conference52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
Country/TerritoryUnited States
CityPacific Grove
Period10/28/1810/31/18

Keywords

  • Compound K-distribution
  • curve fitting
  • estimation
  • intensity moments
  • sea clutter
  • thermal noise power

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Estimation of Compound K-distribution Modeling Parameters of Sea Clutter with Unknown Thermal Noise Power'. Together they form a unique fingerprint.

Cite this