Abstract
Antenna arrays with high directivity, low side-lobe level, and null control in desired direction and whip antenna with wider bandwidth both need to be optimized to meet different needs of communication systems. A new natural heuristic algorithm simulating social behavior of grasshoppers, grasshopper optimization algorithm (GOA), is applied to electromagnetic field as a new effective technology to solve the antenna optimization problem for the first time. Its algorithm is simple and has no gradient mechanism, can effectively avoid falling into local optimum, and is suitable for single-objective and multiobjective optimization problems. GOA is used to optimize the side lobe suppression, null depth, and notch control of arbitrary linear array and then used to optimize the loading and matching network of 10-meter HF broadband whip antenna compared with other algorithms. The results show that GOA has more advantages in side-lobe suppression, null depth, and notch control of linear array than other algorithms and has better broadband optimization performance for HF whip antenna. The pattern synthesis and antenna broadband optimization based on GOA provide a new and effective method for antenna performance optimization.
Highlights
In communication systems, especially in point-to-point communication systems, antennas are required to have fairly strong directionality. e antenna array [1, 2] is mainly used to enhance directivity, improve gain coefficient, or to obtain the required directional characteristics
Six examples from two aspects can more fully reflect the ability of grasshopper optimization algorithm (GOA) in antenna optimization than other methods in the existing literature. e second part of this paper will briefly introduce the optimization principle of GOA. e third part briefly describes the principle of pattern synthesis of linear array and broadband optimization of whip antenna and cites six examples to prove its ability to optimize antenna performance, including suppression of the maximum sidelobe level (SLL), the depth of null depression and the notch of linear array, and design for the loading and matching network of broadband antenna. e fourth part concludes the paper
GOA is applied to antenna optimization in electromagnetic field for the first time
Summary
Especially in point-to-point communication systems, antennas are required to have fairly strong directionality. e antenna array [1, 2] is mainly used to enhance directivity, improve gain coefficient, or to obtain the required directional characteristics. In terms of electromagnetic field problems and antenna optimization, population-based algorithms inspired by nature are the most popular in stochastic optimization methods [4, 5]. A new nature-inspired algorithm, grasshopper optimization algorithm (GOA), is applied to linear antenna array optimization and antenna broadband optimization. GOA is introduced into electromagnetic field for the first time and applied to array pattern synthesis and antenna broadband optimization. E third part briefly describes the principle of pattern synthesis of linear array and broadband optimization of whip antenna and cites six examples to prove its ability to optimize antenna performance, including suppression of the maximum sidelobe level (SLL), the depth of null depression and the notch of linear array, and design for the loading and matching network of broadband antenna. Six examples from two aspects can more fully reflect the ability of GOA in antenna optimization than other methods in the existing literature. e second part of this paper will briefly introduce the optimization principle of GOA. e third part briefly describes the principle of pattern synthesis of linear array and broadband optimization of whip antenna and cites six examples to prove its ability to optimize antenna performance, including suppression of the maximum sidelobe level (SLL), the depth of null depression and the notch of linear array, and design for the loading and matching network of broadband antenna. e fourth part concludes the paper
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