Multi-objective Optimization Design of Tag Antenna Structure Parameters Based on Improved PSO Algorithm
In order to solve the problems of unclear optimization direction and slow optimization speed in antenna structure op-timization by antenna designers using electromagnetic simulation software,the embedded radio frequency identification tag antenna design of dry water meter is taken as an example and a multi-objective optimization method for tag antenna structure parameters based on improved particle swarm optimization(PSO)algorithm is proposed in this paper.Firstly,based on the traceability re-quirements of dry water meter products,four objective functions are proposed:the center frequency point should be as close as pos-sible to the ideal center frequency point,the return loss should be as low as possible,the bandwidth should be as wide as possible,and the area should be as small as possible.Secondly,in order to avoid the local optima of PSO algorithm,methods such as multi-dimensional uniform Latin hypercube initialization,logistic chaotic mapping nonlinear change inertia weight,grid partitioning change learning factor,Gaussian perturbation strategy,etc.are used to improve the algorithm and are applied to multi-objective optimization of tag antenna structural parameters.Finally,an instance validation is conducted.The validation results show that the optimized parameters of the tag antenna structure obtained by the improved PSO algorithm meet the target optimization requirements to a greater extent,and the optimization time is only 40.1%of that of the electromagnetic simulation software.
radio frequency identificationtag antenna structure parametersimproved particle swarm optimization algorithmmulti-objective optimization
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