Influence of unmanned combat aerial vehicle agility on short-range aerial combat effectiveness

The flight agility of an unmanned combat aerial vehicle (UCAV) determines its ability to rapidly transition from one state to another. In this paper, the influence of flight agility on short-range aerial combat effectiveness is quantitatively investigated. This research is based on one-on-one three-...

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Bibliographic Details
Published in:Aerospace science and technology Vol. 96; p. 105534
Main Authors: Wang, Maolin, Wang, Lixin, Yue, Ting, Liu, Hailiang
Format: Journal Article
Language:English
Published: Elsevier Masson SAS 01.01.2020
Subjects:
Aerial combat
Approximate dynamic programming
Flight agility
UCAV
Flight agility
Approximate dynamic programming
Aerial combat
UCAV
ISSN:1270-9638, 1626-3219
Online Access:Get full text
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Summary:The flight agility of an unmanned combat aerial vehicle (UCAV) determines its ability to rapidly transition from one state to another. In this paper, the influence of flight agility on short-range aerial combat effectiveness is quantitatively investigated. This research is based on one-on-one three-dimensional aerial combat engagements. First, a 6-DOF mathematical model of the UCAV is established, and a nonlinear dynamic inverse controller is designed. The flight agility is calculated based on the 180∘ flight heading reverse maneuver, and the influence of the control law parameters is studied. To implement autonomous intelligent aerial combat engagements, a three-dimensional approximate dynamic programming method is proposed. The performance of the designed algorithm is validated through both Monte Carlo simulations with various initial conditions and engagements with another algorithm for comparison. After training, the aerial combat simulation framework is constructed by combining the point-mass-based guidance law and a nonlinear UCAV model. Combat engagements are conducted between UCAVs with different configurations. The quantitative results are evaluated through Monte Carlo simulations and correlation analysis.
ISSN:1270-9638
1626-3219
DOI:10.1016/j.ast.2019.105534