Self-Structuring Antenna Optimization Designs Based On Artificial Intelligence Algorithms

Self-structuring antenna is a novel smart antenna which is capable to change its electric structure according to outer environment or signal strength. This kind of change does not mean to change its physical structure, but means to alter the switches on antenna template. Because of this, self-structuring antenna has been one of hotpot in field of smart antenna recently. In this paper, a series of research of self-structuring antenna are presented as follows:Advantages and disadvantages of genetic algorithm, simulated annealing algorithm and quantum genetic algorithm are analyzed comparatively, an improved genetic simulated annealing algorithm is proposed, as a result of test functions, it has better performance than standard genetic algorithm in global convergence. After that, a scheme of self-structuring antenna optimization using HFSS is designed in MATLAB. The scheme is effective to search the structure of self-structuring antenna. Later, the improved algorithm is used to search structures of patch self-structuring antenna and rectangle loop antenna respectively. In the research of patch antenna, three operating modes: single-frequency, multi-frequency and broadband-frequency are testing respectively, it turns out that the improved algorithm is better than other intelligent algorithms in global optimization when self-structuring antenna is operating in single-frequency mode. Meanwhile, genetic multi-objective algorithm is able to perform well when self-structure antenna is operating in multi-frequency and broadband-frequency. As the change of radiation pattern, another scheme of optimization is proposed in the research of rectangle loop self-structuring antenna. Gain and reflection coefficient of antenna are considered in the scheme together, and it can maintain the characteristics of original radiation pattern in some aspects. Problem of balanced-feed in rectangle loop self-structuring antenna is discussed at last.In this thesis, artificial intelligence algorithm is applied to search electrical structure from self-structuring patch antenna and self-structuring rectangular loop antenna and to analyze their performance. It concluded that self-structuring antenna has the ability to work on single band, multi-band and wideband. Multi-objective optimization algorithm is used on self-structuring antennas to optimize multiple antenna performance parameters. These conclusions have instruction significance in application design and optimization method of self-structuring antenna.