Radar Cross Section Models for Limited Aspect Angle Windows

Abstract

This thesis presents a method for building Radar Cross Section (RCS) models of aircraft based on static data taken from limited aspect angle windows. These models statistically characterize static RCS. This is done to show that a limited number of samples can be used to effectively characterize static aircraft RCS. The optimum models are determined by performing both a Kolmogorov and a Chi-Square goodness-of-fit test comparing the static RCS data with a variety of probability density functions (pdf) that are known to be effective at approximating the static RCS of aircraft. The optimum parameter estimator is also determined by the goodness of-fit tests if there is a difference in pdf parameters obtained by the Maximum Likelihood Estimator (MLE) and the Method of Moments (MoM) estimators. Section, Statistical Modeling.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA258918

Entities

People

  • Mark C. Robinson

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Aspect Angle
  • Data Science
  • Databases
  • Electromagnetic Radiation
  • Estimators
  • Goodness Of Fit Tests
  • Information Science
  • Method Of Moments
  • Probability
  • Probability Density Functions
  • Radar
  • Radar Cross Sections
  • Random Variables
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Readers

  • Computational Modeling and Simulation
  • Radar Systems Engineering.
  • Statistical inference.