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Pattern synthesis of linear antenna-array for high gain and low sidelobe level based on sand cat swarm optimization algorithm

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Abstract

This study presents a novel optimization method based on the sand cat swarm optimization (SCSO) algorithm for the pattern synthesis of linear antenna-array (LAA), aiming to obtain the high gain and low sidelobe level (SLL). The innovation of the proposed method consists in efficiently regulating the radiation characteristics of the LAA by optimizing the geometric and electrical parameters including the phase, amplitude, rotation and position based on the SCSO algorithm to achieve the desired radiation performances. The full-wave method of moments (MoM) is adopted to rigorously consider the mutual coupling effect among the array elements to guarantee the design accuracy. To demonstrate the feasibility and effectiveness of the SCSO algorithm, the proposed method is compared with three typical algorithms, including the Genetic Algorithm (GA), the Gray Wolf (GWO) algorithm, and the Particle Swarm Optimization (PSO). The results show that the SCSO algorithm demonstrates superior convergence capabilities while maintaining the high gain and low SLL, highlighting the potential as a robust method for the LAA.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos: 5217051006), the Natural Science Foundation of Shandong Province (Grant Nos: ZR2021ME223), the Shandong Offshore Engineering Facility & Material Innovation Entrepreneurship Community Project (Grant Nos: GTP-2404) and the Yantai Science Technology Planning Project (Grant Nos: 2022GCCRC158).

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Authors and Affiliations

  1. School of Electromechanical and Automotive Engineering, Yantai University, Yantai, 264000, China

    Jianhui Mou, Jian Wang & Yangwei Wang

  2. JiHai Innovation Shandong Marine Technology Company Limited, Yantai, 264000, China

    Ming Xiang & Lihua Zhang

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  1. Jianhui Mou
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Mou, J., Wang, J., Wang, Y. et al. Pattern synthesis of linear antenna-array for high gain and low sidelobe level based on sand cat swarm optimization algorithm. J Supercomput 81, 318 (2025). https://doi.org/10.1007/s11227-024-06763-w

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