Purpose

The issues of radiating sources in the existence of smooth convex matters by such objects are of huge significance in the modeling of antennas on structures. Conformal antenna arrays are necessary when an antenna has to match to certain platforms. A fundamental problem in the design is that the possible surfaces for a conformal antenna are infinite in number. Furthermore, if there is no symmetry, each element will see a different environment, and this complicates the mathematics. As a consequence, the element factor cannot be factored out from the array factor.

Design/methodology/approach

This paper intends to enhance the design of the conformal antenna. Here, the main objective of this task is to maximize the antenna gain and directivity from the first-side lobe and other side-lobes in the two way radiation pattern. Thus the adopted model is designed as a multiobjective concern. In order to attain this multiobjective function, both the element spacing and the radius of each antenna element should be optimized based on the probability of the Crow Search Algorithm (CSA). Thus the proposed method is named Probability Improved CSA (PI-CSA). Here, the First Null Beam Width (FNBW) and Side-Lobe Level (SLL) are minimized. Moreover, the adopted scheme is compared with conventional algorithms, and the results are attained.

Findings

From the analysis, the gain of the presented PI-CSA scheme in terms of best performance was 52.68% superior to ABC, 25.11% superior to PSO, 13.38% superior to FF and 3.21% superior to CS algorithms. Moreover, the mean performance of the adopted model was 62.94% better than ABC, 13.06% better than PSO, 24.34% better than FF and 10.05% better than CS algorithms. By maximizing the gain and directivity, FNBW and SLL were decreased. Thus, the optimal design of the conformal antenna has been attained by the proposed PI-CSA algorithm in an effective way.

Originality/value

This paper presents a technique for enhancing the design of the conformal antenna using the PI-CSA algorithm. This is the first work that utilizes PI-CSA-based optimization for improving the design of the conformal antenna.

中文翻译：

---

借助概率改进的乌鸦搜索算法的共形天线设计的演变

目的

此类物体存在光滑凸面物质中的辐射源问题在结构天线建模中具有重要意义。当天线必须与某些平台匹配时，共形天线阵列是必要的。设计中的一个基本问题是共形天线的可能表面数量是无限的。此外，如果没有对称性，每个元素都会看到不同的环境，这使数学变得复杂。因此，无法从数组因子中分解出元素因子。

设计/方法/方法

本文旨在加强共形天线的设计。此处，此任务的主要目标是最大化双向辐射方向图中第一旁瓣和其他旁瓣的天线增益和方向性。因此，采用的模型被设计为一个多目标关注点。为了获得这个多目标函数，每个天线单元的单元间距和半径都应该根据 Crow 搜索算法 (CSA) 的概率进行优化。因此，所提出的方法被命名为概率改进的 CSA (PI-CSA)。这里，第一零波束宽度 (FNBW) 和旁瓣电平 (SLL) 被最小化。此外，采用的方案与传统算法进行了比较，得到了结果。

发现

从分析来看，所提出的 PI-CSA 方案在最佳性能方面的增益比 ABC 算法高 52.68%，比 PSO 算法高 25.11%，比 FF 算法高 13.38%，比 CS 算法高 3.21%。此外，所采用模型的平均性能比 ABC 好 62.94%，比 PSO 好 13.06%，比 FF 好 24.34%，比 CS 算法好 10.05%。通过最大化增益和方向性，FNBW 和 SLL 降低。因此，本文提出的PI-CSA算法有效地实现了共形天线的优化设计。

原创性/价值

本文介绍了一种使用 PI-CSA 算法增强共形天线设计的技术。这是第一项利用基于 PI-CSA 的优化来改进共形天线设计的工作。