PDF Approximation for Radar Data.

Abstract

The subject of this report is a new method for approximating the underlying probability density function of random data, called the Osturk Algorithm, and its application to spatial radar clutter data. This algorithm works extremely well with only 100 independent samples.This is an improvement over classical methods which can only determine statistical consistency with a specified distribution and require thousands of independent samples. The efficiency of this algorithm allows the approximation of the probability density function of the spatial clutter data from a much smaller region. This makes it possible to observe changes in clutter statistics over a scan volume. The analysis in this report used the algorithm to approximate how close the data from a clutter measurement experiment was to being Gaussian. This analysis determined that the majority of this spatial clutter data was non-Gaussian. (AN)

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1995
Accession Number
ADA296192

Entities

People

  • John E. Maher
  • Lisa K. Slaski

Organizations

  • Rome Laboratory

Tags

Communities of Interest

  • Advanced Electronics
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Clutter
  • Computational Science
  • Data Analysis
  • Data Science
  • Data Sets
  • Goodness Of Fit Tests
  • Information Science
  • Mathematics
  • Probability
  • Probability Density Functions
  • Radar
  • Radar Clutter
  • Radar Signals
  • Signal Processing
  • Statistics

Readers

  • Computer Vision.
  • Statistical inference.