Antenna Optimization and Design Based on Binary Coding
Junping Geng, Ronghong Jin
gengjunp@sjtu.edu.cn
eBook ISBN978-981-16-7965-0，Hardcover ISBN978-981-16-7964-3
Springer Press, 2022.1
With the rapid development of remote sensing, wireless transmission and radar technique, antenna has the bottleneck of the wireless system. There are ten thousand of researchers and engineers are studying and design antenna. But they mostly design the antenna from their experiences or their original model are from the books or others papers, and then revise the structure or parameters. So, what is the optimum antenna for your design task? It is very difficult to answer. As we said, the design process is disturbed by your prior knowledge and experiences.
In fact, it is impossible to completely abandon our prior knowledge and experience to design antennas. In order to decrease these disturbs, optimization methods are introduced to assist engineers to rapidly design antennas with good performance and to solve the inverse scattering problem of the antenna by constructing the system with rules, aims, and basic units. At present, the optimization methods applied in antenna design mainly include particle swarm algorithm (PSO), genetic algorithm (GA) and simulated annealing algorithm. Based on the long research experience and results of our group, this book focuses on the application of optimization algorithms in multi frequency antenna, low profile antenna, ultra wide band antenna and so on.
In first chapter, we introduce background and the importance of antenna optimization. Then the development and trend of antenna optimization based on AI are discussed. In the second chapter, we emphatically introduced the basic concepts and principles of particle swarm algorithms and improved particle swarm algorithms, as well as the flow of their use, following by a brief description of other optimization algorithms such as GA.
Then in chapters 3 to 9, examples of using optimization algorithms to optimize antenna are explained in detailed. All the results mentioned in this book are published journal, articles and patents by our groups. In the third chapter,a multi-frequency antenna is sussessfully proposed by the steps combining rough designs and precise designs.The condition that the new grids can be only placed near the old one is set to avoid the discontinuity. A-CLPSO is introduced to avoid premature convergence.In the 4th chapter, carved patch antenna part and carved middle ground based on Particle Swarm Optimization (PSO) method is proposed, which can work well on the metal ground at Chinese RFID frequency band—840MHz-845MHz.In the 5th chapters，two parasitic patch are established by grid and optimized by PSO. Placed under the spiral antenna, the antenna requires more broad bandwith, stable radiation pattern and better circular performance. In 6th chapter, a binary-code mm-wave antenna with broadband, dual-polarization and wide beamwidth is proposed. The driven patch and the parasitic patch are formed by series of small rectangular units optimized by binary codes with multi-objects. The designed mm wave antenna element can work from 21.8 to 33.2 GHz. In 7th chapter, we first use the genetic algorithm to optimize the parameters of the UWB antenna. In 8th chapter, discrete hexagon grids in parasitic layer are presented, which guarantee the line-to-line connection between adjacent elements. After optimizing the hexagon grids, a low profile antenna with wide CP bandwidth and stable unidirectional pattern is obtained. In the 9th chapter, the configuration of the particle swarm optimization algorithm is presented. And a continuous and smooth structure generating method is described. In the end, the optimized result and experiment data are analyzed.
