【摘要】：當(dāng)對(duì)天線進(jìn)行優(yōu)化設(shè)計(jì)時(shí),可以結(jié)合電磁仿真軟件HFSS和粒子群優(yōu)化算法予以實(shí)現(xiàn),但是調(diào)用HFSS評(píng)估粒子群算法的適應(yīng)度時(shí)需要花費(fèi)大量的時(shí)間,同時(shí)也對(duì)計(jì)算機(jī)性能有較高的要求,從而對(duì)復(fù)雜結(jié)構(gòu)的天線設(shè)計(jì)造成困難。本文針對(duì)多種用途和頻段的天線,將高斯過(guò)程建模方法融合到粒子群優(yōu)化算法中,對(duì)天線進(jìn)行了優(yōu)化設(shè)計(jì),達(dá)到設(shè)計(jì)指標(biāo)要求;同時(shí)和以往粒子群算法與HFSS軟件相結(jié)合的方法進(jìn)行了比較,證明高斯過(guò)程-粒子群聯(lián)合算法在優(yōu)化時(shí)間上具有極大的優(yōu)勢(shì)。本文主要的研究工作如下:1、介紹了高斯過(guò)程模型的建立方法及評(píng)估方法,以矩形側(cè)饋微帶天線模型為例,表明高斯過(guò)程模型預(yù)測(cè)該天線的頻率特性具有一定的精確性。2、介紹了高斯過(guò)程-粒子群聯(lián)合算法的思路,從時(shí)間的角度將該方法與調(diào)用電磁仿真軟件HFSS作為粒子群算法適應(yīng)度評(píng)價(jià)方案的方法進(jìn)行了對(duì)比,說(shuō)明了高斯過(guò)程-粒子群聯(lián)合算法的優(yōu)勢(shì)。3、對(duì)印刷偶極子天線的頻率特性進(jìn)行高斯過(guò)程建模,解決了有帶寬要求的天線頻率特性建模問(wèn)題,并將此高斯過(guò)程模型融合到粒子群算法中去,對(duì)印刷偶極子天線某些結(jié)構(gòu)的尺寸進(jìn)行優(yōu)化設(shè)計(jì),大幅減少了優(yōu)化設(shè)計(jì)所需時(shí)間。4、對(duì)GPS北斗雙模微帶天線的頻率特性進(jìn)行高斯過(guò)程建模,解決了較窄的頻帶范圍內(nèi)對(duì)特殊頻率點(diǎn)有要求的天線頻率特性建模問(wèn)題,建立起精確度比較高的高斯過(guò)程模型,融合到粒子群算法中,對(duì)該天線結(jié)構(gòu)尺寸進(jìn)行了優(yōu)化設(shè)計(jì),大幅減少了天線優(yōu)化設(shè)計(jì)所需時(shí)間。5、對(duì)雙脊喇叭天線的頻率特性進(jìn)行高斯過(guò)程建模,解決了寬頻帶天線頻率特性建模問(wèn)題,建立起高精度高斯過(guò)程模型,融合到粒子群算法中,對(duì)雙脊喇叭天線結(jié)構(gòu)尺寸進(jìn)行了優(yōu)化設(shè)計(jì),大幅減少了該天線優(yōu)化設(shè)計(jì)所需時(shí)間。
[Abstract]:When the antenna is optimized, it can be realized by combining electromagnetic simulation software HFSS and particle swarm optimization algorithm, but it takes a lot of time to use HFSS to evaluate the fitness of particle swarm optimization algorithm. At the same time, there is a high demand for computer performance, which makes the antenna design of complex structure difficult. In this paper, Gao Si process modeling method is integrated into particle swarm optimization (PSO) algorithm for antenna with various uses and frequency bands, and the antenna is optimized to meet the requirements of the design index. At the same time, the method of combining particle swarm optimization algorithm with HFSS software is compared, and it is proved that the Gao Si process-particle swarm optimization algorithm has great advantages in the optimization time. The main research work in this paper is as follows: 1. The establishment and evaluation methods of Gao Si process model are introduced. Taking the rectangular side-fed microstrip antenna model as an example, it is shown that Gao Si process model has certain accuracy in predicting the frequency characteristics of the antenna. This paper introduces the idea of Gao Si process-Particle Swarm Optimization Joint algorithm, and compares this method with the method of using electromagnetic simulation software HFSS as the fitness evaluation method of Particle Swarm Optimization algorithm from the point of view of time. The advantages of the Gao Si process-particle swarm joint algorithm are illustrated. 3, the Gao Si process modeling for the frequency characteristics of printed dipole antennas is carried out, which solves the problem of antenna frequency characteristics modeling with bandwidth requirements. The Gao Si process model is incorporated into the particle swarm optimization algorithm to optimize the size of some structures of printed dipole antenna, which greatly reduces the time required for optimization design. 4, The frequency characteristics of GPS dual-mode microstrip antenna are modeled by Gao Si process, which solves the problem of antenna frequency characteristic modeling for special frequency points in a narrow band range, and sets up a Gao Si process model with high accuracy. The structure size of the antenna is optimized by the particle swarm optimization algorithm, which greatly reduces the time required for the optimization design of the antenna. 5. The frequency characteristics of the antenna with double ridged horn are modeled by Gao Si process. The problem of frequency characteristic modeling of broadband antenna is solved. A high precision Gao Si process model is established and incorporated into particle swarm optimization algorithm. The structural size of the antenna with double ridged horn is optimized, which greatly reduces the time required for the optimum design of the antenna.
【學(xué)位授予單位】：江蘇科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN820;TP18

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