Pattern Synthesis Design of Linear Array Antenna with Unequal Spacing Based on Improved Dandelion Optimization Algorithm Article Swipe
Jianhui Li
,
Yan Liu
,
Wanru Zhao
,
TianNing Zhu
,
Zhuo Chen
,
Anyong Liu
,
Yibo Wang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25030861
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25030861
With the rapid development of radio technology and its widespread application in the military field, the electromagnetic environment in which radar communication operates is becoming increasingly complex. Among them, human radio interference makes radar countermeasures increasingly fierce. This requires radar systems to have strong capabilities in resisting electronic interference, anti-radiation missiles, and radar detection. However, array antennas are one of the effective means to solve these problems. In recent years, array antennas have been extensively utilized in various fields, including radar, sonar, and wireless communication. Many evolutionary algorithms have been employed to optimize the size and phase of array elements, as well as adjust the spacing between them, to achieve the desired antenna pattern. The main objective is to enhance useful signals while suppressing interference signals. In this paper, we introduce the dandelion optimization (DO) algorithm, a newly developed swarm intelligence optimization algorithm that simulates the growth and reproduction of natural dandelions. To address the issues of low precision and slow convergence of the DO algorithm, we propose an improved version called the chaos exchange nonlinear dandelion optimization (CENDO) algorithm. The CENDO algorithm aims to optimize the spacing of antenna array elements in order to achieve a low sidelobe level (SLL) and deep nulls antenna pattern. In order to test the performance of the CENDO algorithm in solving the problem of comprehensive optimization of non-equidistant antenna array patterns, five experimental simulation examples are conducted. In Experiment Simulation Example 1, Experiment Simulation Example 2, and Experiment Simulation Example 3, the optimization objective is to reduce the SLL of non-equidistant arrays. The CENDO algorithm is compared with DO, particle swarm optimization (PSO), the quadratic penalty function method (QPM), based on hybrid particle swarm optimization and the gravity search algorithm (PSOGSA), the whale optimization algorithm (WOA), the grasshopper optimization algorithm (GOA), the sparrow search algorithm (SSA), the multi-objective sparrow search optimization algorithm (MSSA), the runner-root algorithm (RRA), and the cat swarm optimization (CSO) algorithms. In the three examples above, the SLLs obtained using the CENDO algorithm optimization are all the lowest. The above three examples all demonstrate that the improved CENDO algorithm performs better in reducing the SLL of non-equidistant antenna arrays. In Experiment Simulation Example 4 and In Experiment Simulation Example 5, the optimization objective is to reduce the SLL of a non-uniform array and generate some deep nulls in a specified direction. The CENDO algorithm is compared with the DO algorithm, PSO algorithm, CSO algorithm, pelican optimization algorithm (POA), and grey wolf optimizer (GWO) algorithm. In the two examples above, optimizing the antenna array using the CENDO algorithm not only results in the lowest SLL but also in the deepest zeros. The above examples both demonstrate that the improved CENDO algorithm has better optimization performance in simultaneously reducing the SLL of non-equidistant antenna arrays and reducing the null depth problem. In summary, the simulation results of five experiments show that the CENDO algorithm has better optimization ability in the comprehensive optimization problem of non-equidistant antenna array patterns than all the algorithms compared above. Therefore, it can be regarded as a strong candidate to solve problems in the field of electromagnetism.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s25030861
- OA Status
- gold
- Cited By
- 2
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4407037911
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4407037911Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/s25030861Digital Object Identifier
- Title
-
Pattern Synthesis Design of Linear Array Antenna with Unequal Spacing Based on Improved Dandelion Optimization AlgorithmWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-31Full publication date if available
- Authors
-
Jianhui Li, Yan Liu, Wanru Zhao, TianNing Zhu, Zhuo Chen, Anyong Liu, Yibo WangList of authors in order
- Landing page
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https://doi.org/10.3390/s25030861Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.3390/s25030861Direct OA link when available
- Concepts
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Radar, Antenna (radio), Antenna array, Algorithm, Radiation pattern, Computer science, Interference (communication), Electronic engineering, Particle swarm optimization, Engineering, Telecommunications, Channel (broadcasting)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
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34Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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