Cooperative Behavior Schemes for Improving the Effectiveness of Autonomous Wide Area Search Munitions

Abstract

The problem being addressed is how to best find and engage an unknown number of targets in unknown locations using multiple autonomous wide area search munitions. In this research cooperative behavior is being investigated to improve the overall mission effectiveness. A simulation was used to emulate the behavior of autonomous wide area search munitions and measure their overall expected performance. This code was modified to incorporate the capability for cooperative engagement based on a parameterized decision rule. Using Design of Experiments and Response Surface Methodologies, the simulation was run to achieve optimal decision rule parameters for given scenarios and to determine the sensitivities of those parameters to the precision of the Autonomous Target Recognition algorithm, lethality of the warhead, and the characteristics of the battlefield. Results show that the form of cooperative engagement used in this study is most useful in overcoming the limitations on warhead lethality and, to a lesser degree, probability of target report. However, cooperative engagement alone is not able to compensate for higher false target attack rates. Also, the selection of the optimal weights in the decision algorithm are very sensitive to all battlefield characteristics.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2001
Accession Number
ADA390167

Entities

People

  • Daniel P. Gillen

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Analysis Of Variance
  • Basic Programming Language
  • Computer Simulations
  • Detection
  • Engineering
  • Experimental Design
  • False Targets
  • Identification
  • Munitions
  • Recognition
  • Simulations
  • Statistics
  • Target Recognition
  • Targets
  • Weapons

Readers

  • Computational Modeling and Simulation
  • Explosive Engineering.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.