A Jamming Scheme Decision-making Method Based on Artificial Bee Colony Algorithm
Aiming at the problem of multiple unmanned jamming platforms cooperating with active jamming against multiple active radar-guided threat targets,a quantitative model of jamming effect e-valuation is built by comprehensively considering the similarities and differences between UAV and USV and the performance of both jamming parties.For the evaluation of jamming effectiveness of the jamming party,four classes of evaluation indicators are established,including jamming suppression probability,jamming working frequency band,quantity of jamming patterns and jamming effective space.For the threat degree evaluation of missile targets,four classes of evaluation indicators are estab-lished,including the target speed,distance,pitch angle and altitude.The traditional artificial bee colony algorithm(ABC)is further improved by chaotic mapping strategy to optimize the solution of the jamming scheme decision-making model.The simulation results show that the proposed jamming deci-sion-making method can effectively allocate jamming resources,and the improved artificial bee colony algorithm(I ABC)can effectively improve the optimization rate compared with the traditional ABC algo-rithm.
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