Unmanned Aerial Vehicle Contributions to Intelligence, Surveillance, and Reconnaissance Missions for Expeditionary Operations

Abstract

This study analyzes the impact of unmanned aerial vehicle (UAV) capabilities on intelligence gathering missions for a Marine Expeditionary Brigade (MEB) commander in 2015. The Marine Corps Warfighting Lab (MCWL) is developing requirements for an intelligence, surveillance, and reconnaissance (ISR) UAV that supports rapid planning and decision making for multiple concurrent operations and facilitates maneuver and precision engagement. The acquisition of a 2008 Pioneer replacement also is underway at Marine Corps Systems Command (MARCORSYSCOM). However, the importance of various capabilities for this replacement UAV presently lacks quantitative analysis. Through modeling, agent-based simulation, and data mining, this study explores the validity of current requirements and provides insights into the importance of various UAV characteristics, such as airspeed, endurance, sweep width, and sensor capability. Each year, the Navy/Marine Corps conducts Fleet Battle Experiment Sea Viking in Southern California. The primary objective is Command and Control and ISR development. This study looks at UAV operations in the Sea Viking scenario provided by MCWL in the MANA agent-based modeling environment utilizing robust design, Latin hypercubes, data farming techniques, the Maui High Performance Computing Center, and the JMP Statistical Discovery Software package. The Sea Viking Experiment, the Marine Corps' largest annual experiment, provides a credible scenario for model development. The advantages of tactical routing, a 7 hour (or greater) on-station time, a minimum 4,500 meter sweep width, and a probability of classification of at least 0.4 are verified for the Sea Viking scenario. This analysis indicates that a UAV in this scenario does not need to travel in excess of 200 knots. The results have design consequences for MCWL's Sea Viking 20XX and provide key parameters for physics-based simulations such as COMBAT XXI. A 15-item bibliography is included. (26 figures, 26 refs7

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2004
Accession Number
ADA427707

Entities

People

  • Mark Raffetto

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • C4I
  • Ground and Sea Platforms
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Agent-Based Simulations
  • Aircrafts
  • Computational Science
  • Data Mining
  • Databases
  • Experimental Design
  • Geographic Regions
  • Geography
  • Graphical User Interface
  • Information Science
  • Iraqi-War
  • Military Science
  • Reconnaissance
  • Regression Analysis
  • Test And Evaluation
  • Unmanned Aerial Vehicles
  • Warfare

Readers

  • Computational Modeling and Simulation
  • Maritime Combat Support and Expeditionary Logistics.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - UAVs
  • Fully Networked C3
  • Fully Networked C3 - Command and Control