基于遗传算法的天线阵阵列综合技术研究

Research on Synthesis Technology of Antenna Array Based on GA

在实际工程中,通常根据应用需求可预先设计好天线阵方向图,然后根据该方向图反向推导出天线阵单元馈电的幅度、相位信息。然而由于天线阵单元数目较多以及所需波束形状复杂很难用常规的方法推导阵列单元馈电的信息。针对该问题设计了遗传算法来解决。将天线阵单元馈电的幅度、相位信息等效为生物种群。基于该种群设计了遗传变异算法模型,这些算法模型充分模拟了自然界生物种群的基因突变、基因重组和染色体变异,满足物竞天择、适者生存的自然法则,达到天线阵阵列综合优化设计目标。此外,依据该遗传变异模型编写了相应的程序。通过遗传算法优化的方向图与目标方向图在主瓣内相差小于1d B,从而验证了设计的遗传算法模型的准确性。

In reality, the antenna array pattern can be designed in advance according to the application requirements, and then the amplitude and phase information of the array element feeding can be deduced inversely according to the pattern. However, due to the large number of array elements and the complex beam shapes, it is difficult to calculate the amplitude and phase information of the array element excitation by conventional methods. A genetic algorithm is designed to solve this problem. The amplitude and phase information fed by the antenna array are equivalent to biological populations. Based on this population, genetic mutation algorithm models are designed. These algorithm models fully simulate the gene mutation, gene recombination and chromosomal mutation of natural biological populations, meet the natural laws of natural selection and survival of the fittest, Perfectly achieves the goal of antenna array synthesis technology. In addition, corresponding programs were written according to the designed genetic variation models. In the main lobe range, the difference between the pattern optimized by the genetic algorithm and the actual pattern is less than 1dB, which verifies the accuracy of the designed genetic algorithm model.