Dynamic target assignment method for UCAV fleet using memory enhanced dynamic UMDA

Xing Guang Peng; Xiao Guang Gao

doi:10.3969/j.issn.1001-506X.2010.10.32

Dynamic target assignment method for UCAV fleet using memory enhanced dynamic UMDA

Xing Guang Peng, Xiao Guang Gao

School of Electronics and Information

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Aiming at the dynamic target assignment problem in anti-ground mission of an unmanned combat aerial vehicle (UCAV) fleet, a weapon target assignment (WTA) model for associated targets is built up. A memory enhanced dynamic univariate marginal distribution algorithm (MDUMDA) is proposed to solve the problem at hand. In this algorithm, the probability model is utilized to save and reuse the historic evolutionary information. Simulation results show that the WTA model is reasonable, the MDUMDA can effectively solve dynamic WTA, and its performance is significantly better than the random immigration algorithm.

Original language	English
Pages (from-to)	2166-2170
Number of pages	5
Journal	Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
Volume	32
Issue number	10
DOIs	https://doi.org/10.3969/j.issn.1001-506X.2010.10.32
State	Published - Oct 2010

Keywords

Dynamic univariate marginal distribution algorithm (UMDA)
Dynamic weapon target assignment (WTA)
Memory method
Unmanned combat aerial vehicle (UCAV) fleet

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Cite this

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abstract = "Aiming at the dynamic target assignment problem in anti-ground mission of an unmanned combat aerial vehicle (UCAV) fleet, a weapon target assignment (WTA) model for associated targets is built up. A memory enhanced dynamic univariate marginal distribution algorithm (MDUMDA) is proposed to solve the problem at hand. In this algorithm, the probability model is utilized to save and reuse the historic evolutionary information. Simulation results show that the WTA model is reasonable, the MDUMDA can effectively solve dynamic WTA, and its performance is significantly better than the random immigration algorithm.",

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AU - Gao, Xiao Guang

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AB - Aiming at the dynamic target assignment problem in anti-ground mission of an unmanned combat aerial vehicle (UCAV) fleet, a weapon target assignment (WTA) model for associated targets is built up. A memory enhanced dynamic univariate marginal distribution algorithm (MDUMDA) is proposed to solve the problem at hand. In this algorithm, the probability model is utilized to save and reuse the historic evolutionary information. Simulation results show that the WTA model is reasonable, the MDUMDA can effectively solve dynamic WTA, and its performance is significantly better than the random immigration algorithm.

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Dynamic target assignment method for UCAV fleet using memory enhanced dynamic UMDA

Abstract

Keywords

UN SDGs

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