A New Hybrid Equivalent Modeling Method of Low-Frequency Radiation Source Based on GS and JADE Algorithms and Phaseless Near-Field Data

Near-field phase measurements are often difficult and very time-consuming for real applications in comparison with phaseless ones. Meanwhile, it is also challenging, with global optimization or phase recovery algorithm implemented, to build an equivalent radiation model based on a dipole array throu...

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Published inIEEE transactions on electromagnetic compatibility Vol. 66; no. 3; pp. 917 - 927
Main Authors Huang, Xiaoting, Liu, Qifeng, Chen, Hao, Li, Yongming, Huang, Chen, Zhu, Xuegui, Zhang, Huaiqing, Yin, Wen-Yan
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN0018-9375
1558-187X
DOI10.1109/TEMC.2024.3359259

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Summary:Near-field phase measurements are often difficult and very time-consuming for real applications in comparison with phaseless ones. Meanwhile, it is also challenging, with global optimization or phase recovery algorithm implemented, to build an equivalent radiation model based on a dipole array through phaseless near-field data. The optimization and phase recovery algorithms have certain problems in the selections of dipole moment limits and local optimality, respectively. Here, a new hybrid equivalent modeling method of low-frequency radiation characteristics is proposed, which combines the Gerchberg-Saxton (GS) algorithm with adaptive differential evolution algorithm effectively. An initial set of dipole arrays with dipole position, array height, and dipole moment is obtained using the fast solution of the GS algorithm at first, and global optimization algorithm is further used to update the dipole arrays with the global seeking to improve both accuracy and efficiency of the equivalent modeling for the low-frequency radiation source. Such hybrid method can solve the problem of the GS algorithm, which is easy to fall into the local optimum, as well as the problem of global optimization algorithm not being able to quickly determine upper and lower bounds of dipole moments. Its effectiveness is verified by simulations as well as measurements.
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ISSN:0018-9375
1558-187X
DOI:10.1109/TEMC.2024.3359259