Target allocation algorithm in formation cooperative air-to-ground attacking based on IBPSO

Qing Jun Xia; An Zhang; Yao Zhong Zhang

doi:10.3969/j.issn.1001-506X.2010.09.32

Target allocation algorithm in formation cooperative air-to-ground attacking based on IBPSO

Qing Jun Xia, An Zhang, Yao Zhong Zhang

School of Aeronautics

Northwestern Polytechnical University Xian

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

Abstract

According to the characteristics of target allocation in formation cooperative air-to-ground combat (FCAGC), some issues about the application of improved binary particle swarm optimization (IBPSO) to target allocation are studied. Firstly, by computing the income and cost of damaging targets, an evaluation standard of target allocation is set up. Secondly, the formulas about the velocity and position of binary particle swarm optimization are improved by introducing into a series of operators. Then, IBPSO is applied to target allocation. Simulation results show that IBPSO has a more powerful global search capability and faster convergence velocity than the genetic algorithm (GA).

Original language	English
Pages (from-to)	1937-1940
Number of pages	4
Journal	Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
Volume	32
Issue number	9
DOIs	https://doi.org/10.3969/j.issn.1001-506X.2010.09.32
State	Published - Sep 2010

Keywords

Formation cooperative air-to-ground combat (FCAGC)
Improved binary particle swarm optimization (IBPSO)
Soft kill weapon system
Target allocation

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10.3969/j.issn.1001-506X.2010.09.32

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title = "Target allocation algorithm in formation cooperative air-to-ground attacking based on IBPSO",

abstract = "According to the characteristics of target allocation in formation cooperative air-to-ground combat (FCAGC), some issues about the application of improved binary particle swarm optimization (IBPSO) to target allocation are studied. Firstly, by computing the income and cost of damaging targets, an evaluation standard of target allocation is set up. Secondly, the formulas about the velocity and position of binary particle swarm optimization are improved by introducing into a series of operators. Then, IBPSO is applied to target allocation. Simulation results show that IBPSO has a more powerful global search capability and faster convergence velocity than the genetic algorithm (GA).",

keywords = "Formation cooperative air-to-ground combat (FCAGC), Improved binary particle swarm optimization (IBPSO), Soft kill weapon system, Target allocation",

author = "Xia, {Qing Jun} and An Zhang and Zhang, {Yao Zhong}",

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AU - Zhang, An

AU - Zhang, Yao Zhong

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N2 - According to the characteristics of target allocation in formation cooperative air-to-ground combat (FCAGC), some issues about the application of improved binary particle swarm optimization (IBPSO) to target allocation are studied. Firstly, by computing the income and cost of damaging targets, an evaluation standard of target allocation is set up. Secondly, the formulas about the velocity and position of binary particle swarm optimization are improved by introducing into a series of operators. Then, IBPSO is applied to target allocation. Simulation results show that IBPSO has a more powerful global search capability and faster convergence velocity than the genetic algorithm (GA).

AB - According to the characteristics of target allocation in formation cooperative air-to-ground combat (FCAGC), some issues about the application of improved binary particle swarm optimization (IBPSO) to target allocation are studied. Firstly, by computing the income and cost of damaging targets, an evaluation standard of target allocation is set up. Secondly, the formulas about the velocity and position of binary particle swarm optimization are improved by introducing into a series of operators. Then, IBPSO is applied to target allocation. Simulation results show that IBPSO has a more powerful global search capability and faster convergence velocity than the genetic algorithm (GA).

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KW - Improved binary particle swarm optimization (IBPSO)

KW - Soft kill weapon system

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JF - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics

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Target allocation algorithm in formation cooperative air-to-ground attacking based on IBPSO

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