基于遗传-蚁群融合算法的干扰资源分配方法

Method of jamming resource distribution based on genetic-ant colony fusion algorithm

针对多部干扰机协同干扰多部雷达的干扰资源分配问题,提出一种基于遗传-蚁群融合算法的干扰资源分配算法。首先采用综合集成赋权法结合逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)对目标雷达进行威胁评估,然后建立干扰资源多约束优化分配模型,最后采用遗传-蚁群融合算法对模型进行求解。融合算法利用遗传算法快速寻找出若干组优化解,将这些优化解用于调整蚁群算法中初始信息素的分布,利用蚁群算法对问题进一步优化,从而找到最优解,提升了算法的求解精度和求解时间。仿真结果表明,融合算法的性能在收敛速度和寻优准确性等方面相较于其他算法都有了较大提升。

Aiming at the jamming resource distribution when multiple jammers work together to jam multiple radars,a method of jamming resource distribution is proposed based on the genetic-ant colony fusion algorithm.First of all,a threat assessment of the target radar is worked out by means of the metasynthesis weight method and the technique for order preference by similarity to an ideal solution(TOPSIS).Then,a multi-constraint optimization model for jamming resource is established.Ultimately,the proposed genetic-ant colony fusion algorithm is used to compute the distribution model.The fusion algorithm finds out several optimal solutions quickly by the genetic algorithm.Meanwhile,these optimal solutions are employed to adjust the distribution of the initial pheromones in the ant colony algorithm.The ant colony algorithm is utilized to further refine the issue,so as to obtain the optimal solution.The accuracy of the fusion algorithm is improved and the time of processing is decreased by this way.The simulation results reveal that the property of the genetic-ant colony fusion algorithm has been substantially ameliorated compared to other algorithms in terms of convergence speed and calculation accuracy.