Optimal Deployment of Distant Support Jamming Formation Based on Directional Crossover Genetic Algorithm

doi:10.16182/j.issn1004731x.joss.201806033

Abstract

Abstract: Optimal deployment of distant support jamming formation is studied for improving penetration capability of air assault group in air offensive operation. The total detection threats of penetration route are chosen as the performance indicator, and the optimal deployment mode of distant support jamming formation is built. The closed region detection method is used to compute fitness value. The difficult problem of computing detection coverage of radar net under jamming condition is solved by using traditional geometry analytic method. A selective directional crossover genetic algorithm is designed to compute the optimal deployment mode. The simulation results show that the algorithm has stronger global searching capability and faster convergence speed than nonlinear crossover genetic algorithm for which the computation performance is better at present.

Key words: air offensive operation, distant support jamming, optimal deployment, selective direction crossover, real-coded genetic algorithm

CLC Number:

TN972

Luo Jinliang, Jin Jiacai, Wang Lei, Ding Feng. Optimal Deployment of Distant Support Jamming Formation Based on Directional Crossover Genetic Algorithm[J]. Journal of System Simulation, 2018, 30(6): 2263-2271.

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