Publication:
Probability Modeling of Autonomous Unmanned Combat Aerial Vehicles (UCAVs)

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Authors
Kress, Moshe
Baggesen, Arne
Gofer, Eylam
Subjects
unmanned systems
strike warfare
Markov processes
Advisors
Date of Issue
2006
Date
2006-05
Publisher
Language
Abstract
Unmanned Combat Aerial Vehicles (UCAVs) are advanced weapon systems that can loiter autonomously in a pack over a target area, detect and acquire the targets, and then engage them. Modeling these capabilities in a specific hostile operational setting is necessary for addressing weapons' design and operational issues. In this paper we develop several analytic probability models, which range from a simple regenerative formula to a large-scale continuous-time Markov chain, with the objective to address the aforementioned issues. While these models capture key individual aspects of the weapon such as detection, recognition, memory and survivability, special attention is given to pack related aspects such as simultaneous targeting, multiple kills due to imperfect battle damage assessment, and the effect of attack coordination. From implementing the models we gain some insights on design and operational consideration regarding the employment of a pack of UCAVs in a strike scenario.
Type
Article
Description
Military Operations Research, Vol. 11, No. 4, pp 5-24.
Series/Report No
Department
Operations Research (OR)
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Citation
2006 “Probability Modeling of Autonomous Unmanned Combat Aerial Vehicles (UCAVs)” (with A. Baggesen and E. Gofer), Military Operations Research, Vol. 11, No. 4, pp 5-24.
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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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