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Improved dandelion optimizer for sparse array antenna beam pattern synthesis

Published online by Cambridge University Press:  16 October 2025

Ruiyou Li Open the ORCID record for Ruiyou Li [Opens in a new window] ,
Min Li ,
Yong Zhang  and
Long Zhang
Ruiyou Li*
Affiliation:
School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, China
Min Li
Affiliation:
School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, China
Yong Zhang
Affiliation:
School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, China
Long Zhang
Affiliation:
School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang, China
*
Corresponding author: Ruiyou Li; Email: liruiyou@jxufe.edu.cn
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Abstract

The existing intelligent optimization algorithms face challenges related to premature convergence in the synthesis of array antennas, resulting in low solution accuracy and a tendency to get stuck in local optima. In this paper, a logistic chaos and spiral flight dandelion optimizer (LSDO) algorithm is applied to sparse antenna array synthesis with constraints. To optimize the positions of the array elements and reduce sidelobe levels, the logistic chaotic mapping is employed for population initialization, which generates a diverse and uniformly distributed initial population. Additionally, the dandelion optimizer (DO) algorithms utilize a spiral flight strategy to enhance local exploitation capability and escape from the local optimum of the sidelobe level. For algorithm performance, numerical experimental results show the stability and robustness of the LSDO algorithm. For the optimization of planar sparse arrays, the LSDO algorithm significantly outperforms conventional optimization methods, achieving a peak sidelobe level (PSLL) reduction of 15.5% for DO, 9% for PSO, and 14.56% for IWO. These results confirm the effectiveness and superiority of the proposed algorithm.

Keywords

dandelion optimizerlogistic chaotic mappeak sidelobe levelsparse arrayspiral flight

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Type
Research Paper
Information
International Journal of Microwave and Wireless Technologies , First View , pp. 1 - 11
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Copyright
© The Author(s), 2025. Published by Cambridge University Press in association with The European Microwave Association.

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References

Agha, MH, Al-Adwany, MAS, Bayat, O and Hamdoon, HT (2022) Optimization of antenna array pattern for uniformly excited rectangular array via a thinning method[J]. Journal of King Saud University-Engineering Sciences 34(8), 544–561. https://doi.org/10.1016/j.jksues.2021.02.003CrossRefGoogle Scholar
Hong, Y, Shao, W, Lv, YH, Wang, BZ, Peng, L and Jiang, B (2022) Knowledge-based neural network for thinned array modeling with active element patterns[J]. IEEE Transactions on Antennas and Propagation 70(11), 11229–11234. https://doi.org/10.1109/TAP.2022.3187518CrossRefGoogle Scholar
Pan, S, Lin, M, Xu, M, Zhu, S, Bian, LA and Li, G (2021) A low-profile programmable beam scanning holographic array antenna without phase shifters[J]. IEEE Internet of Things Journal 9(11), 8838–8851. https://doi.org/10.1109/JIOT.2021.3116158CrossRefGoogle Scholar
Brandt-Møller, M, Mattes, M, Breinbjerg, O, Zhou, M and Jørgensen, E (2024) Extended higher-order array decomposition method for fully populated or thinned array antennas and scatterers with connected elements[J]. IEEE Transactions on Antennas and Propagation 72(5), 4454–4464. https://doi.org/10.1109/TAP.2024.3380251CrossRefGoogle Scholar
Buonanno, G, Costanzo, S and Solimene, R (2023) Broadband statistically designed thinned-binned array antennas[J]. IEEE Transactions on Antennas and Propagation 71(3), 2454–2466. https://doi.org/10.1109/TAP.2023.3236793CrossRefGoogle Scholar
Li, PF, Qu, SW, Yang, S and Hu, J (2022) Low-scattering-cross section thinned phased array antenna based on active cancellation technique[J]. IEEE Transactions on Antennas and Propagation 70(7), 5481–5490. https://doi.org/10.1109/TAP.2022.3161303CrossRefGoogle Scholar
Wang, J, Wu, X, Ye, J, Sun, J and Hua, G (2024) A novel two-way pattern synthesis method with the uniform and thinned arrays[J]. IEEE Antennas and Wireless Propagation Letters.CrossRefGoogle Scholar
Mitha, TH and Pour, M (2022) Sidelobe reductions in linear array antennas using electronically displaced phase center antenna technique[J]. IEEE Transactions on Antennas and Propagation 70(6), 4369–4378. https://doi.org/10.1109/TAP.2021.3138499CrossRefGoogle Scholar
Zhang, J, Mao, X, Zhang, M, Hirokawa, J and Liu, QH (2022) Synthesis of thinned planar arrays based on precoded subarray structures[J]. IEEE Antennas and Wireless Propagation Letters 22(1), 44–48. https://doi.org/10.1109/LAWP.2022.3201382CrossRefGoogle Scholar
Rahardjo, ET, Sandi, E and Zulkifli, FY Design of linear sparse array based on the Taylor line source distribution element spacing[C]//2017 IEEE Asia Pacific Microwave Conference (APMC). IEEE, 2017: 61–64.CrossRefGoogle Scholar
Lou, M, Jin, J, Wang, H, Wu, D, Xia, L, Wang, Q, Yuan, Y and Wang, J (2022) Performance analysis of sparse array based massive MIMO via joint convex optimization[J]. China Communications 19(3), 88–100. https://doi.org/10.23919/JCC.2022.03.006CrossRefGoogle Scholar
Lee, Y (2020) Adaptive interference suppression of phase-only thinned arrays via convex optimization[J]. IEEE Transactions on Antennas and Propagation 68(6), 4583–4592. https://doi.org/10.1109/TAP.2020.2977732CrossRefGoogle Scholar
Kedar, A, Vangol, P and Mahesh, A Hybridization of Bayesian compressive sensing and array dilation technique for synthesis of linear Isophoric sparse antenna arrays[J]. IEEE Transactions on Antennas and Propagation, 2023.CrossRefGoogle Scholar
Li, W, Zhang, Y and Shi, X (2019) Advanced fruit fly optimization algorithm and its application to irregular subarray phased array antenna synthesis[J]. IEEE Access 7, 165583–165596. https://doi.org/10.1109/ACCESS.2019.2953544CrossRefGoogle Scholar
He, Y and Wang, C (2023) Optimization design for sparse planar array in satellite communications[J]. Electronics 12(8), 1763. https://doi.org/10.3390/electronics12081763CrossRefGoogle Scholar
Elkhawaga, AM, Mahmoud, NM, AbdElnaby, MM and Hussein, AH (2022) New hybrid approaches for SLL reduction and size miniaturization of planar antenna arrays based on 2D convolution and genetic algorithm[J]. Alexandria Engineering Journal 61(9), 7233–7264. https://doi.org/10.1016/j.aej.2021.12.065CrossRefGoogle Scholar
Mevada, P, Gupta, S, Chakrabarty, S and Mahajan, M (2022) Design of beam-steerable aperiodic linear array antenna with improved peak SLL using strip-projection method[J]. IEEE Transactions on Antennas and Propagation 70(7), 5430–5436. https://doi.org/10.1109/TAP.2022.3146865CrossRefGoogle Scholar
Karasev, AS and Stepanov, MA Genetic algorithm for antenna array thinning with minimization of side lobe level[C]//2021 XV International Scientific-Technical Conference on Actual Problems Of Electronic Instrument Engineering (APEIE). IEEE, 2021: 268–272.CrossRefGoogle Scholar
Zheng, Y, You, CJ, Zhang, N, Zhu, X, Ding, Y and He, H (2024) Wide-angle scanning thinned phased array synthesis based on improved multi-objective beluga whale optimization algorithm[J]. IEEE Antennas and Wireless Propagation Letters. 23(11), 3511–5.CrossRefGoogle Scholar
Vankayalapati, S, Lakshman, P, Kumar, K, Batch, NV, Dalali, A, Inti, ND and Netinti, NR (2022) Application of binary particle swarm optimization algorithm for thinned planar antenna array synthesis[C]//2022 8th international conference on advanced computing and communication systems (ICACCS). IEEE, 1: 1414–1418.Google Scholar
Liang, Q, Chen, B, Wu, H, Ma, C and Li, S (2021) A novel modified sparrow search algorithm with application in side lobe level reduction of linear antenna array[J]. Wireless Communications and Mobile Computing 2021, 1–25. https://doi.org/10.1155/2021/9915420CrossRefGoogle Scholar
Owoola, EO, Xia, K, Ogunjo, S, Mukase, S and Mohamed, A (2022) Advanced marine predator algorithm for circular antenna array pattern synthesis[J]. Sensors 22(15), 5779. https://doi.org/10.3390/s22155779CrossRefGoogle ScholarPubMed
Owoola, EO, Xia, K, Wang, T, Umar, A and Akindele, RG (2021) Pattern synthesis of uniform and sparse linear antenna array using mayfly algorithm[J]. IEEE Access 9, 77954–77975. https://doi.org/10.1109/ACCESS.2021.3083487CrossRefGoogle Scholar
Srinivasareddy, S, Narayana, YV and Krishna, D (2021) Sector beam synthesis in linear antenna arrays using social group optimization algorithm[J]. National Journal of Antennas and Propagation 3(2), 6–9.Google Scholar
Guo, YJ, Ansari, M and Fonseca, NJG (2021) Circuit type multiple beamforming networks for antenna arrays in 5G and 6G terrestrial and non-terrestrial networks[J]. IEEE Journal of Microwaves 1(3), 704–722. https://doi.org/10.1109/JMW.2021.3072873CrossRefGoogle Scholar
Ikram, M, Sultan, K, Lateef, MF and Alqadami, AS (2022) A road towards 6G communication—A review of 5G antennas, arrays, and wearable devices[J]. Electronics 11(1), 169. https://doi.org/10.3390/electronics11010169CrossRefGoogle Scholar
Zhao, S, Zhang, T, Ma, S and Chen, M (2022) Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications[J]. Engineering Applications of Artificial Intelligence 114, 105075. https://doi.org/10.1016/j.engappai.2022.105075CrossRefGoogle Scholar
Fu, J, Wu, C, Wang, J, Haque, MM, Geng, L and Meng, J (2024) Lithium-ion battery SOH prediction based on VMD-PE and improved DO optimized temporal convolutional network model[J]. Journal of Energy Storage 87, 111392. https://doi.org/10.1016/j.est.2024.111392CrossRefGoogle Scholar
He, J, Guo, W, Wang, S, Chen, H, Guo, X and Li, S (2024) Application of multi-strategy based improved do algorithm in optimal scheduling of reservoir groups[J]. Water Resources Management 1–19.Google Scholar
Li, J, Liu, Y, Zhao, W and Zhu, T (2024) Application of dandelion optimization algorithm in pattern synthesis of linear antenna arrays[J]. Mathematics 12(7), 1111. https://doi.org/10.3390/math12071111CrossRefGoogle Scholar
Li, J, Liu, Y, Zhao, WR, Zhu, T, Wang, Y and Hu, K (2024) Sidelobes and sideband minimization in time-modulated array antenna based on chaotic exchange nonlinear dandelion optimization algorithm[J]. Scientific Reports 14(1), 19150. https://doi.org/10.1038/s41598-024-70222-yCrossRefGoogle ScholarPubMed
Li, J, Liu, Y, Zhu, TN and Zhao, W (2023) Optimize linear antenna arrays with dandelion optimization algorithm[C]//2023 IEEE 13th international conference on electronics information and emergency communication (ICEIEC). IEEE, 144–147.Google Scholar
Hu, G, Zheng, Y, Abualigah, L and Hussien, AG (2023) DETDO: An adaptive hybrid dandelion optimizer for engineering optimization[J]. Advanced Engineering Informatics 57, 102004. https://doi.org/10.1016/j.aei.2023.102004CrossRefGoogle Scholar
Han, S, Zhu, K and Wang, R (2021) Improvement of evolution process of dandelion algorithm with extreme learning machine for global optimization problems[J]. Expert Systems with Applications 163, 113803. https://doi.org/10.1016/j.eswa.2020.113803CrossRefGoogle Scholar
Khalil, AE, Boghdady, TA, Alham, MH and Ibrahim, DK (2024) A novel cascade-loop controller for load frequency control of isolated microgrid via dandelion optimizer[J]. Ain Shams Engineering Journal 15(3), 102526. https://doi.org/10.1016/j.asej.2023.102526CrossRefGoogle Scholar
Liu, X and Qin, X (2020) A probability-based core dandelion guided dandelion algorithm and application to traffic flow prediction[J]. Engineering Applications of Artificial Intelligence 96, 103922. https://doi.org/10.1016/j.engappai.2020.103922CrossRefGoogle Scholar