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J Electromagn Eng Sci > Epub ahead of print
[Epub ahead of print] Published online July 14, 2021.
Optimal Design of Thinned Array Using a Hybrid Genetic Algorithm
Sang-Hoon Jung1, Kang-In Lee2, Hyun-Su Oh2, Hyun-Kyo Jung1, Hoongee Yang2, Young-Seek Chung2
1Department of Electrical and Computer Engineering, Seoul National University, Korea
2Department of Electronic Convergence Engineering, Kwangwoon University, Korea
Correspondence:  Young-Seek Chung,Email: yschung@kw.ac.kr
Received: 10 September 2020   • Revised: 6 January 2021   • Accepted: 2 March 2021
In this paper, a hybrid genetic algorithm (GA) is proposed for thinning a two-dimensional planar array by combining the conventional GA with moving least squares (MLS). This enhances the convergence rate and the global search performance. The MLS method is used to estimate local interpolation functions from non-uniform sample data (the population and the value of the objective function in the GA), and to find new and better populations from the interpolated functions. By incorporating these improved populations into the next generation, the MLS-GA achieves improved search performance of the global optimum and a faster convergence rate compared to conventional GA alone. Moreover, a non-linear chirp function is used for an efficient thinning design. To verify the proposed MLS-GA, it is applied to a test function and the results are compared to that of the GA. The algorithm is then applied to thin an array with a rectangular grid and circular boundary. The design objectives are to minimize the peak side-lobe level and gain loss while satisfying a given thinning coefficient and to compare the results with the GA.
Key words: Array signal processing, Hybrid genetic algorithms, Moving least square method, Thinned array antenna, Wave propagation
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