基于约束差分进化的阵列置零

发布时间：2018-01-17 18:25

本文关键词：基于约束差分进化的阵列置零　出处：《微波学报》2017年05期 　论文类型：期刊论文

【摘要】：阵列置零的同时,阵列的旁瓣电平升高、主瓣增益降低甚至阵列指向都会发生改变,导致阵列性能降低。针对阵列置零时阵列性能降低问题,提出一种约束优化模型。在约束优化模型中不仅设置了零陷深度约束和近旁瓣电平约束,还设置了阵列期望方向增益约束及阵列指向约束。在满足约束条件下,使得阵列旁瓣电平最低。并且针对标准约束差分进化算法收敛慢,采用自适应约束差分进化(ε-SADE)算法,该算法采用多种变异方式相结合、自适应地调节交叉概率和缩放因子。运用自适应约束差分进化分别通过调节阵元相位和阵列功率一定时的阵元权值求解这个约束优化问题,仿真结果表明提出的方法实现了需求的目标方向图,利用自适应约束差分进化算法优化实现阵列置零是有效可行的。
[Abstract]:While the array is zero, the sidelobe level of the array increases, the main lobe gain decreases and even the array direction changes, which results in the array performance degradation. A constraint optimization model is proposed, in which not only the depth constraints and sidelobe constraints are set, but also the desired directional gain constraints and the array direction constraints are set. In order to reduce the sidelobe level of the array, the adaptive constrained differential evolution (蔚 -SADE) algorithm is used to solve the problem of slow convergence of the standard constrained differential evolution algorithm, which combines multiple mutation methods. The crossover probability and scaling factor are adjusted adaptively. Adaptive constrained differential evolution is used to solve the constrained optimization problem by adjusting the element weight when the phase and power of the array are fixed respectively. The simulation results show that the proposed method realizes the target pattern of the requirement, and the adaptive constrained differential evolution algorithm is effective and feasible to optimize the array zeroing.
【作者单位】：西北工业大学电子信息学院;
【基金】：航空基金(20142053025)
【分类号】：TN820;TP18
【正文快照】： 引言阵列天线广泛应用于雷达、通信、射电天文等众多领域[1]。阵列置零是一种常见的阵列综合问题,但是在调节阵元权值实现阵列置零的同时,会改变阵列方向图,导致阵列旁瓣升高,阵列增益降低等。现有的大部分研究[2-4]将旁瓣、零陷、近旁瓣等多个目标,用加权求和方式组成适应度

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