Using Fuzzy Logic in Evaluating User Tabled Correlation Rules for COMINT

Abstract

This paper presents a methodology for performing level-1 fusion involving organizational structures and for determining which structures, if any, can be recognized. Available data consists of contact reports received via various communications circuits. Information for correlation arises from three main sources: parametric signature data such as radio frequency, nominative categorical information such as unit identifier, and location information such as intercept position. Both individual and aggregations of such data separately give rise to correlation sub-scores. Each sub-score provides evidence about whether a new report correlates with an existing entity. The paper identifies methods and reports some preliminary results correlation, which use the operators of fuzzy logic, and adaptive weighting to enforce analysts specified correlation rules.

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Document Details

Document Type
Technical Report
Publication Date
May 17, 2000
Accession Number
ADA392900

Entities

People

  • John M. Palmer

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Ambiguity
  • Classification
  • Control Systems
  • Correlation Techniques
  • Correlators
  • Data Science
  • Discriminant Analysis
  • Environment
  • Frequency
  • Fuzzy Logic
  • Identification
  • Information Science
  • Logic
  • Organizational Structure
  • Test And Evaluation

Readers

  • Computational Linguistics
  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Regression Analysis.