Prediction of Electromagnetic Scattering for Rough Terrain Using Statistical Parameters Derived from Digitized Topographic Maps,

Abstract

For terrain which is gently undulating and whose surface height excursions are large compared to a wavelength, well known formulas for the normalized bistatic cross section as a function of the polarization states of the incident and scattered EM waves are available in the literature. There are also several theoretical models which describe the EM scattering cross section of surfaces characterized by two scales of roughness. The present analysis applies parameter estimation techniques to a digitized topographic data base. The results are used in a hypothesis test to determine the best probability density function (PDF) for the given map data. The accuracy of the analysis depends on the available data, the estimators employed, and the determination of appropriate PDF's. The example which will be discussed consists of a large number of terrain regions in an area of eastern Massachusetts. This area was chosen because experimental data in the form of electromagnetic forward scattering from the surface are available. Because of the number of cases involved, the complexity of the multivariate height distributions, and the type of measurements available, only a single observation of the multivariate data is used in the present analysis. The results of the statistical analysis for mean height, variance, correlation, PDF, and a geologic feature characterizing each subregion are presented.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1980
Accession Number
ADA094104

Entities

People

  • J. F. Lennon
  • R. J. Papa
  • R. L. Taylor

Organizations

  • Rome Laboratory

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Beacons
  • Computer Programs
  • Computers
  • Covariance
  • Data Science
  • Databases
  • Dielectric Permittivity
  • Electromagnetic Scattering
  • Experimental Data
  • Information Science
  • Probability
  • Probability Density Functions
  • Radar
  • Scattering
  • Statistical Analysis
  • Transmitters

Readers

  • Computer Vision.
  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Statistical inference.