基于实数编码遗传算法的方向图模值综合方法

Pattern synthesis with desired magnitude response based on real coded genetic algorithm

提出一种基于实数编码遗传算法的方向图综合方法,采用近亲交叉回避机制和自适应交叉变异概率等,避免了基本遗传算法过早收敛的缺点。与传统的对模值和相位均进行约束的综合方法相比,本方法不仅能够有效地获取期望方向图,而且主瓣控制机制与参考点的选取无关,综合得到的方向图与期望的方向图之间的误差较小。计算机仿真表明该算法的有效性与正确性。

A novel pattern synthesis method based on the improved real coded genetic algorithm is proposed. The closed crossing avoidance and self-adapting crossover and mutation rate are used to avoid the prema-ture and slow convergent speed of the standard genetic algorithm. Compared with the traditional pattern synthe-sis algorithms which synthesize the array patterns with both desired magnitude and phase response, the presented algorithm, which synthesizes the array patterns with only desired magnitude response, is not only efficient but also independent of the reference points. Computer simulations demonstrate the effectiveness and validity of the proposed algorithm.