Numerical Estimation of Marcum's Q-Function using Monte Carlo Approximation Schemes

Abstract

The Marcum Q-Function is an important tool in the study of radar detection probabilities in Gaussian clutter and noise. Due to the fact that it is an intractable integral, much research has focused on finding good numerical approximations for it. Such approximations include numerical integration techniques, such as adaptive Simpson quadrature, and Taylor series approximations, induced by the modified Bessel function of order zero, which appears in the integrand. One technique which has not been explored in the literature is the sampling-based Monte Carlo approach. Part of the reason for this is that the integral representation of the Marcum Q-Function is not in the most suitable form for Monte Carlo methods. Using some recently derived techniques, we construct a number of sampling-based estimators of this function, and we consider their relative merits.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2006
Accession Number
ADA451869

Entities

People

  • Graham V. Weinberg
  • Louise Panton

Organizations

  • Defence Science and Technology Group

Tags

Communities of Interest

  • Electronic Warfare
  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Data Science
  • Detection
  • Distribution Functions
  • Electronic Warfare
  • Engineering
  • Estimators
  • Information Processing
  • Information Science
  • Monte Carlo Method
  • Network Science
  • Random Variables
  • Standards
  • Statistical Algorithms
  • Statistical Sampling
  • Warfare

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Radar Systems Engineering.
  • Statistical inference.