| 摘要: |
| 针对自卫电子对抗中干扰任务分配对资源使用效率的问题，以“一对一”干扰为例，首先构建了干扰任务分配流程，并建立任务程度模型与干扰任务过滤模型，通过二次过滤筛选得到对我方威胁度大且能够被有效干扰的目标；然后根据节约干扰资源的原则，建立以总干扰功率最小为目标函数的干扰任务分配模型；最后采用二进制GPSO（Genetic-Particle Swarm Optimization）算法进行求解，提高了得到最优解的收敛速度、精度以及全局搜索能力。仿真表明，提出的干扰任务分配模型可以较好地筛除威胁程度低及干扰程度小的目标，节约了不必要的资源从而提高了资源的利用率。 |
| 关键词: 自卫电子对抗 干扰资源 任务分配 干扰任务过滤 粒子群算法 |
| DOI： |
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| 基金项目:航空科学基金（20152096019） |
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| Implication of secondary filtration model for jamming task allocation |
| GUO Pengcheng,WANG Xing,CHENG Siyi,WANG Yubing |
| () |
| Abstract: |
| For the problems of jamming resource efficiency in self-defense electronic countermeasures,taking a “one to one” jamming for example,this paper establishes a flow of jamming task allocation firstly,and builds task level model and jamming task filtration model to choose the specific targets by secondary filtration. Based on the principle of saving jamming resource,a jamming task allocation model is set up with the minimum jamming power. Finally,the model is solved through binary Genetic-Particle Swarm Optimization(GPSO) to improve the rate of convergence,accuracy and global search capacity. Simulation result demonstrates that the proposed model can remove targets with low threat level and low jamming level,and has improved the use ratio of jamming resources. |
| Key words: self-defense electronic countermeasures jamming resource task allocation jamming task filtration particle swarm optimization algorithm |
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