On M-ary Sequential Hypotheses Testing for the Classification of Radar Signals.

Abstract

This report is concerned with the performance of M-ary sequential hypothesis tests applied to the classification of radar signals. In the first part of this report, several available M-ary sequential algorithms are considered. These include the algorithms due to Reed, Armitage and Palmer. Modifications of the existing algorithm are considered and their effects on the average number of required measurements and the resulting error performance are examined. Three other techniques are also proposed, a tree algorithm and a sequential maximum a posteriori test as well as a sequential version of the various algorithms by means of Monte-Carlo simulations of the radar signal observations. The performance of these techniques is compared and the relative merits of each algorithm are discussed.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1987
Accession Number
ADA184094

Entities

People

  • F. D. Garber
  • Ismail Jouny

Organizations

  • Ohio State University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Catalogs
  • Databases
  • Distribution Functions
  • Electrical Engineering
  • Identification
  • Identification Systems
  • Low Noise
  • Pattern Recognition
  • Power Levels
  • Probability
  • Radar
  • Radar Signals
  • Radar Targets
  • Recognition
  • Simulations

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Radio communications and signal processing.
  • Regression Analysis.