Modeling Cognitive and Tactical Aspects in Hunter - Killer Missions

Abstract

In this thesis, we present a Markov-based probability model for a human operated system of aerial hunter-killers attacking time-sensitive targets. We explore the effect of two resources time and supply of munitions and some cognitive aspects of the human operator on the performance of the system in different operational scenarios. We model the combat mission as a sequence of engagements; each of which includes a classification process, followed by a firing decision, and a shooting process. The model of the classification process addresses possible effects of stress on the operator's behavior and performance. Two shooting tactics are considered. The random shooting tactic, which is memory-less and with no fire control, BDA capability or mission support systems, sets a benchmark for more effective shoot-look-shoot tactic, where resources are utilized more efficiently. The model represents various tactical parameters regarding rules of engagement and various mixes of resources. Applying the model on some real-world scenarios, we identify mixes of resources and tactical engagement rules that enhance the effectiveness and efficiency of the combat mission.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2006
Accession Number
ADA460445

Entities

People

  • Ohad Berman

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms
  • Human Systems
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aerial Warfare
  • Air Force
  • Aircrafts
  • Anti-Tank Missiles
  • Cognition
  • Fighter Aircraft
  • Micro Air Vehicles
  • Military Research
  • Munitions
  • Operations Research
  • Reconnaissance
  • Rules Of Engagement
  • Synthetic Aperture Radar
  • Unmanned Aerial Vehicles
  • Warfare
  • Weapons
  • Weapons Effects

Readers

  • Marksmanship and Weaponry.
  • Military Science
  • Neural Network Machine Learning.