Combat Identification Modeling Using Robust Optimization Techniques

Abstract

The purposes of this research were: (1) the modeling of a CID situation and (2) the search for robust and controllable input variable settings. The inputs were defined as controllable and noise variables and the confusion matrices in ROC theory were adapted to act as controllable factors. In this research a simple virtual battlespace representation is employed. The experimental results of the CID system are summarized by a posterior confusion matrix and throughout the confusion matrix analysis we can obtain all various types of data such as accuracy, error cost, error rates, and so forth. To find the optimal parameters three evaluation techniques were applied: (1) Linearly constrained discrete optimization, (2) Taguchi's S|N ratio method and (3) Robust parameter design with a combined array. The results are compared and contrasted across different objective functions.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2008
Accession Number
ADA482836

Entities

People

  • Taeho Kim

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms
  • Human Systems
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Combat Simulations
  • Computational Science
  • Department Of Defense
  • Detection
  • Detectors
  • Engineering
  • Estimators
  • Identification
  • Information Science
  • Linear Programming
  • Optimization
  • Probability Distributions
  • Regression Analysis
  • Unmanned Aerial Vehicles
  • Warfare

Readers

  • Computer Vision.
  • Regression Analysis.