基于贝叶斯算法的天线端到端优化

doi:10.12305/j.issn.1001-506X.2021.12.01

Abstract

Abstract:

Once the topology of an antenna is determined, optimization of various antenna parameters is conducted to achieve the desired objectives. A fast and effective optimization algorithm is significant to shorten the antenna design period. With the use of a comprehensive objective function which fuses multiple targets and constraints into one single function, the antenna is optimized end-to-end by employing Bayesian optimization algorithm. Based on the online updated dataset, the Gaussian process estimates the posterior distribution of the comprehensive objective function, and afterwards acquisition function is utilized for the iteration. To demonstrate the proposed method, two antenna models are simulated and optimized. The results show that because the proposed method is implemented in an end-to-end way through a mapping from the antenna parameters to a comprehensive objective function, it can achieve better optimization results and higher optimization efficiency compared with the conventional methods.

Key words: antenna optimization, multi-objective optimization, end-to-end, Bayesian optimization algorithm

CLC Number:

TN82

Chunming TIAN, An YANG, Le YE, Jianxing LI, Yuchen HE. End-to-end antenna optimization based on Bayesian optimization algorithm[J]. Systems Engineering and Electronics, 2021, 43(12): 3413-3419.

Figures/Tables 11

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References 31

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序号	真实值	后验均值	后验标准差
1	-70.85	-68.19	3.49
2	-56.49	-55.50	7.98
3	-73.23	-69.23	8.25
4	-84.03	-73.95	4.36
5	-82.06	-82.83	2.61

实验序号	优化后目标函数值	最大S11/dB	最大AR/dB	最小gain/dB
1	6.43	-12.17	2.63	6.23
2	7.39	-17.73	2.66	6.42
3	5.45	-17.79	2.68	6.09

序号	真实值	后验均值	后验标准差
1	18.01	16.64	2.03
2	6.21	7.23	2.08
3	8.47	8.69	3.42
4	14.50	13.00	2.18
5	4.82	5.53	2.10

实验序号	优化后目标函数值	max (S11)/dB	mean (Gain)/dB
1	21.89	-14.47	6.59
2	21.57	-15.42	6.50
3	21.90	-13.96	6.63

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End-to-end antenna optimization based on Bayesian optimization algorithm

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