The Use of Classifiers and Microprocessors for Target Identification Using Millimeter Wave Signatures.

Abstract

The problem of implementing three basic classification techniques for target acquisition in millimeter wave guided weapon systems is discussed in this report. The three classifiers are: (1) the maximum likelihood classifier, (2) the nearest neighbor classifier, and (3) the linear classifier. The mathematics of each classifier is explicitly delineated in order to assess memory storage and computation load requirements. Using these results, the applicability of microprocessors for implementing these classifiers into fieldable systems is considered. It is shown that the classifiers are easily adaptable to experimental target signatures and that the use of microprocessors is requisite. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Apr 26, 1979
Accession Number
ADA074840

Entities

People

  • P. Martin Alexander

Tags

Communities of Interest

  • Advanced Electronics
  • Human Systems
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Algorithms
  • Artificial Intelligence
  • Aspect Angle
  • Computations
  • Guided Weapons
  • Military Research
  • Millimeter Waves
  • Pattern Recognition
  • Probability
  • Probability Distributions
  • Radar
  • Target Acquisition
  • Target Recognition
  • Target Signatures
  • Warfare

Fields of Study

  • Computer science
  • Physics

Readers

  • Computer Vision.
  • Parallel and Distributed Computing.
  • Software Engineering

Technology Areas

  • 5G