School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China.
Department of Physics, Federal University of Technology, Akure 340271, Ondo State, Nigeria.
Sensors (Basel). 2022 Aug 2;22(15):5779. doi: 10.3390/s22155779.
The pattern synthesis of antenna arrays is a substantial factor that can enhance the effectiveness and validity of a wireless communication system. This work proposes an advanced marine predator algorithm (AMPA) to synthesize the beam patterns of a non-uniform circular antenna array (CAA). The AMPA utilizes an adaptive velocity update mechanism with a chaotic sequence parameter to improve the exploration and exploitation capability of the algorithm. The MPA structure is simplified and upgraded to overcome being stuck in the local optimum. The AMPA is employed for the joint optimization of amplitude current and inter-element spacing to suppress the peak sidelobe level (SLL) of 8-element, 10-element, 12-element, and 18-element CAAs, taking into consideration the mutual coupling effects. The results show that it attains better performances in relation to SLL suppression and convergence rate, in comparison with some other algorithms for the optimization case.
天线阵列的模式综合是增强无线通信系统有效性和可靠性的一个重要因素。本工作提出了一种先进的海洋捕食者算法（AMPA），用于合成非均匀圆形天线阵列（CAA）的波束模式。AMPA 利用自适应速度更新机制和混沌序列参数来提高算法的探索和开发能力。简化和升级了 MPA 结构，以克服陷入局部最优的问题。AMPA 用于联合优化幅度电流和单元间间距，以抑制 8 单元、10 单元、12 单元和 18 单元 CAA 的峰值旁瓣电平（SLL），同时考虑互耦效应。结果表明，在优化情况下，与其他一些算法相比，它在 SLL 抑制和收敛速度方面具有更好的性能。
