基于自适应遗传算法的电子支援侦察搜索方式设计

电子支援侦察是雷达对抗侦察的重要组成部分,主要借助已有情报信息对高威胁目标进行核实精测,对时效性和精确性具有较高的要求。传统的搜索方式多为周期步进或区间搜索,与电子支援侦察的任务特性和搜索要求并未完全契合,面对不同环境和任务的灵活性较差。文中基于自适应遗传算法对电子支援侦察的搜索方式进行设计:每一条染色体对应一种侦察搜索方式,染色体的基因值和基因位分别对应该时刻侦察系统的侦察区间和侦察系统在不同区间的停留顺序,以截获概率为适应度函数进行染色体的诱导变异,得到的最优染色体即为当前环境和任务下的最佳搜索方式。理论推导和实验仿真验证了该搜索方式的可行性和有效性。

Search Strategy Design for Electronic Support Measure Based on Adaptive Genetic Algorithm

Electronic support measure is an important part of radar reconnaissance, mainly through existing intelligence information on the high level threat emitters to make high precision measurement or verification. Such operation heavily demands on timeliness and accuracy. Traditional search mode tends to be periodic pattern or stayed on certain region, which is not fully fit with the emitters'' characteristics or the task requirement and possesses poor flexibility. Based on the adaptive genetic algorithm, this paper designs and analyzes the search strategy of electronic support measure. Each chromosome corresponds to a search strategy; the gene value of the chromosome and the position of the gene corresponds to the search intervals and the dwell sequence of search strategy separately. Based on the fitness function, which is calculated by the intercept probability, chromosomes take induced mutation to find the optimal offspring which is also the desired search strategy confronted with the current environment. Theoretical derivation and experimental simulation verify the feasibility and effectiveness of this method.