Antenna design method based on neural network

Abstract

The invention discloses an antenna design method based on a neural network, comprising the steps of constructing an antenna initial model; an RBF neural network and PSO algorithm parameters are initialized; several groups of antenna design parameters are selected and input into the initial antenna model to obtain the corresponding antenna model response; the fitness function value of RBF neural network parameters and the optimal value of algorithm are calculated; the optimal parameters of RBF neural network are obtained; the RBF neural network model is tested and optimized; the optimized RBF neural network model is used as the proxy model to simulate the response of antenna design parameters, and the antenna design is completed. The invention can effectively improve the prediction accuracyand the convergence speed of the neural network, The optimal neural network is used as a proxy model to fit the electromagnetic simulation data of antenna design parameters, which can replace the time-consuming electromagnetic simulation to achieve the instantaneous approximate calculation from antenna structural parameters to electromagnetic response, reduce the number of electromagnetic simulation, reduce the computational cost and improve the efficiency of antenna design.

Description

technical field [0001] The invention specifically relates to a neural network-based antenna design method. Background technique [0002] With the vigorous rise of various communication technologies, wireless communication systems are developing rapidly towards multi-functionality and large capacity. The development of modern wireless communication systems not only requires antennas to be light-weight, low-cost, easy to manufacture, and easy to integrate, but also puts forward more requirements for antenna miniaturization, wide-band, multi-band, conformal, and integrated designs. [0003] Conventional antenna design is generally based on regular structures, using existing empirical formulas, combined with the design experience of antenna engineers and physical measurement and debugging. However, it is obvious that the existing antenna design process has a long design cycle and is very dependent on the designer's personal quality and experience; at the same time, more importa...

AI Technical Summary

Problems solved by technology

Although the evaluation of the model using electromagnetic simulation software ensures a high accuracy of antenna performance prediction, it takes a long time to perform an antenna simulation, especially when designing complex antennas

Especially when optimizing antenna parameters with the help of intelligent optimization algorithms, it may be necessary to call electromagnetic simulation software hundreds of times for simulation calculations, and the time for each EM simulation varies from a few minutes to tens of minutes for different antenna complexities. This means that the time cost of antenna design is too large, which obviously hinders the direct application of intelligent optimization algorithms in the design process, and indirectly leads to the development of various strategies aimed at reducing computational costs.

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