Manned and unmanned aircraft effectiveness in fast attack craft / fast inshore attack craft ASUW kill chain execution

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Authors
Anderson, Alexander D.
Subjects
unmanned aerial vehicles
manned aircraft
kill chain
surveillance
detection
SIMIO
Advisors
Nussbaum, Daniel A.
Atkinson, Michael P.
Date of Issue
2016-09
Date
Sep-16
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
The ability of unmanned aerial vehicles to execute intelligence, surveillance, reconnaissance, and targeting and strike missions creates a trade-space decision for naval aviation programmatic decision makers. In the military's current fiscal climate, manned and unmanned aircraft compete for limited funding. This study takes a simulation approach using the simulation modeling framework based on intelligent objects (SIMIO) environment to model a fast attack craft/fast inshore attack craft anti-surface warfare expanded kill chain. It tests and analyzes multiple manned and unmanned aircraft configurations. In the evaluation of unclassified concepts of operation and use of unclassified data sources, results indicate that aircraft attrition due to hostile weapon engagements is the dominant factor in the determination of concept of operation efficiency. Based on the operational environment, low cost and less capable unmanned aircraft provide an alternative to the increased survivability of manned aircraft or more capable and higher cost unmanned aircraft. We provide quantifiable metrics that enable the efficient and effective selection of aircraft to execute fast attack craft/fast inshore attack craft anti-surface warfare kill chains.
Type
Thesis
Description
Series/Report No
Department
Operations Research
Organization
Identifiers
NPS Report Number
Sponsors
Funder
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Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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