Target Identification by Means of Low Frequency Radar Returns.

Abstract

A target identification technique is presented. It is based on low frequency radar returns. A large variety of objects is shown to be reliably classified in the presence of substantial amounts of noise. The target complexity varies form cylinders and cubes to modern combat airplanes. Two classification algorithms are used and compared, a linear discriminant method and a nearest neighbor rule. Both multiclass and pairwise classifications are carried out and extensively illustrated. The majority of results presented involve only the amplitudes of the radar returns, but the last part of the report describes the very impressive effects of phase on classification performance. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 01, 1974
Accession Number
AD0783224

Entities

People

  • A. A. Ksienski
  • Ying-Tsong Lin

Organizations

  • Ohio State University

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Aircrafts
  • Airplanes
  • Algorithms
  • Amplitude
  • Classification
  • Fixed Wing Aircraft
  • Frequency
  • Identification
  • Mathematics

Readers

  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Neural Network Machine Learning.