Genetic algorithms can appropriately optimize patch antenna arrays for radio astronomy array parameters and patch parameters are optimized separately. Examples of patch antenna enhancements using geneticalgorithm optimizers a gabased optimizer was used to create feedline networks for different shapes of patch antennas. Application of genetic algorithm for optimization of. Examples of patch antenna enhancements using genetic algorithm optimizers a gabased optimizer was used to create feedline networks for different shapes of patch antennas. Aerospace component design is an expensive and important step in space development. In the design, the genetic algorithm is employed to generate the excitation amplitudes of the antenna array. However, the necessity to conform to a predefined shape e. A complete explanation regarding the design of sierpinski bowtie antenna with its behavior has been presented. Nonuniform spacing signal processing antenna array planar arrays array synthesis through genetic algorithm ga. Implementation of the simple genetic algorithm sga this section describes our first optimization approach, which involves the implementation of a simple genetic algorithm sga. Design and optimization of proximity coupled antenna using.
Patch antenna miniaturization through electromagnetic genetic. Conformal antennas and antenna arrays arrays have become necessary for vehicular communications where a high degree of aerodynamic drag reduction is needed, like in avionics and ships. Over the past decade, the air force research laboratory afrl antenna technology branch at hanscom afb has employed the simple genetic algorithm sga as an optimization tool for a wide variety of antenna applications. The work uses genetic algorithms for finding an optimal solution to this problem. Accuracy of the results encourages the use of genetic. An adaptive, phaseonly genetic algorithm applied to a computer model of a linear array has been reported previously. Eas have emerged as viable candidates for global optimization problems and have been attracting the attention of the research community interested in solving realworld engineering problems, as evidenced by the fact that very large number of antenna design problems have been addressed. Keywords antenna arrays, uniform arrays, nonuniform arrays, binomial arrays, dolphchebyshev arrays, genetic algorithm. Optimization of the performance of patch antennas using. Touhami, and tajeddin elhamadi abstractthe miniaturization of the patch antenna has become an important issue in reducing the volume of entire communication system. A new project based on ga and high frequency simulation software hfss is proposed to perform optimization. A genetic algorithm usually encodes each parameter in a binary sequence called ii gene and places the genes in an array known as a chromosome. It is designed by using genetic algorithms with the advantage of not requiring a feeding network. The rectangular patch antenna is analyzed, and what is learned here will be applied to understanding pifas planar invertedf antennas.
The genetic algorithm repeatedly modifies a population of individual solutions. May 22, 2017 a novel pattern of fractal antenna deploying swastika slotted geometry up to second iteration is used for optimization in this paper which enhanced its utilities for sband. In this case, antenna was assumed to be operating in the fundamental tm11 mode. Measured results for the dualband antenna are compared to numerical results. Genetic algorithm, particle swarm optimization and accelerated particle swarm optimization is dealt with. Patch antenna miniaturization through electromagnetic genetic algorithm optimization. A highdirectivity microstrip patch antenna design by using genetic algorithm optimization jeevani w. Various existing optimization algorithms can come handy in this case and genetic algorithm which is one of the global optimization algorithms has been used widely in the past by antenna designers 4 for the optimization of the patch shape and size in order to achieve better overall performance of the antenna. Microstrip patch antenna having a rectangular profile. Recall that our antenna system consists of three sections, each containing eight complex weights i. Experimental adaptive nulling with a genetic algorithm. A parallel electromagnetic geneticalgorithm optimization ego. The above equation says that the microstrip antenna should have a length equal to one half of a wavelength within the dielectric substrate medium. In radio communications, an evolved antenna is an antenna designed fully or substantially by an automatic computer design program that uses an evolutionary algorithm that mimics darwinian evolution.
Here a and a e are the radius and effetive c radius of microstrip patch respectively. Application of genetic algorithm to the optimization of gain of magnetized ferrite microstrip antenna neela chattoraj and jibendu sekhar roy abstractthe application of genetic algorithm ga to the optimization of gain of microstrip antenna, fabricated on ferrite substrate, biased externally by a steady magnetic field, is reported. Jun 08, 2000 a design procedure for a dual feed network is presented to produce a circular polarised matched antenna involving eight design parameters with associated constraints. At each step, the genetic algorithm selects individuals at random from the. Ga analysis of parameters of magnetically biased microstrip. Automated antenna design with evolutionary algorithms.
Each satellite has two communication antennas to talk to ground stations. The design of a broadband patch antenna is a good candidate problem for geneticalgorithm optimizers because a large number of discrete and continuous and dependent parameters exist that are easily handled with gaoptimizers. In this section, well discuss the microstrip antenna, which is also commonly referred to as the patch antenna. An example of an evolved antenna is an xband antenna evolved for a 2006 nasa mission called space technology 5 st5. Patch has been modeled on liti ferrite substrate of thickness h. Genetic algorithm optimization of a highdirectivity microstrip patch.
It is followed, in ord er, by the dolphchebyshev and binomial arrays. At this point the genetic algorithm has to be stopped 1516. Keywords differential algorithm, cavity analysis, microstrip antenna, shortcircuited patch. In addition to a discussion of nearfield measurement and the highfrequency method, this book also covers. The center frequency will be approximately given by. Many antenna types have been investigated, including antenna arrays4 and quadri lar helical antennas. In antenna design problems, the three most commonly used softcomputational algorithms are. Introduction a patch antenna is a metallic strip or a patch mounted on a dielectric layer substrate, which is supported by a ground plane. Multiobjective genetic algorithm approach for a dualfeed. Design of nonuniform antenna arrays using genetic algorithm. Theory a microstrip patch antenna consists of a very thin metallic patch usually gold or copper placed a.
Genetic algorithm optimization for microstrip patch. Genetic algorithms in antennas and smart antennas design. Supernec is a hybrid mom, utd uniform theory of diffraction antenna and. Clearly, radiation patch, substrate, and ground pad can be equivalent to a low impedance microstrip. Uduwawala4 1department of electronics, wayamba university of sri lanka, kuliyapitiya, sri lanka 2technology and intellectual property rights department, fractus, barcelona, spain. Genetic algorithms are commonly used to generate highquality solutions to optimization and search problems by relying on bioinspired operators such as mutation, crossover and. In section 5 we discuss existing approaches to sat3 problem. Crooked wire antenna linden and altshuler search for rhcp antenna that radiates over hemisphere with 7wire antenna confined to. Design and optimization of aperture coupled microstrip patch. A representative patch antenna design example for commercial wireless applications is detailed, which illustrates the versatility and applicability of the method. Antenna theory and microstrip antennas electronic resource. Ill use the terms microstrip antenna and patch antenna interchangeably. I am working on fractals and i am using ga for optimization of my patch antenna. Genetic algorithm in microstrip antenna using matlab.
It explains how the genetic algorithm is implemented through actual antenna arrays for direction of arrival estimation algorithm within the smart antenna systems. Genetic algorithms are commonly used to generate highquality solutions to optimization and search problems by relying on bioinspired operators. Optimizations of patch antenna arrays using genetic algorithms. Introduction the performance of a singleelement antenna is somewhat limited. Genetic algorithm, electromagnetic optimizer highlights on parametric variation of the antenna. The genetic algorithm is implemented on a pc that controls the eightelement cylindrical array. Sat3 is an npcomplete problem for determining whether there exists a solution satisfying a given boolean formula in the conjunctive normal form, wherein each clause has at most three literals. The structure involves 22 design parameters with associated constraints, and a multiobjective genetic algorithm is developed to determine the parameter values. Ga optimization of highdirectivity microstrip patch antennas and miniature.
Apr 22, 2010 genetic algorithm ga is utilized to design microstrip patch antenna shapes for broad bandwidth. Genetic algorithm optimization of a highdirectivity. Laboratory results are largely consistent with simulation. A single highdirectivity microstrip patch antenna mpa having a rectangular profile, which can substitute a linear array is proposed. Line model improvement and extension to the cavity model design procedure of a single rectangular microstrip patch antenna example of ltcc. The script above shows a very simple genetic algorithm applied to the array synthesis problem. For instance, x,y32,1 can be encoded as chromosome 0000000 1. Abstract genetic algorithm ga is utilized to design microstrip patch antenna shapes for broad bandwidth. Genetic algorithm optimization and performance comparative. Functions for the fitness of the ga program is developed using transmission line model of the analysis of microstrip antenna. The circular patch microstrip antenna was modeled using the cavity method of analysis and the fitness functions to optimize the gain and efficiency were obtained. A design procedure for a dual feed network is presented to produce a circular polarised matched antenna involving eight design parameters with associated constraints. The optimized patch design exhibits a threefold enhancement in bandwidth when. Existing approaches of this problem take exponential time and are also memory inefficient.
Patch antenna miniaturization through electromagnetic. Patch antenna shape design using the genetic algorithm. Antenna arrays, patch antennas, antenna optimizations, genetic algorithms. The miniaturization of the patch antenna has become an important issue in reducing the volume of entire communication system. The second shows a twinpatch antenna and its corresponding feedline. Genetic algorithm optimization applied to planar and wire. Genetic algorithm for geometry optimization of optical antennas. Military antenna design using simple and competent genetic. Genetic algorithm ga is utilized to design microstrip patch antenna. The second shows a twin patch antenna and its corresponding feedline. Denote that l and w are the length and width of radiation patch. Genetic algorithms and method of moments gamom for the design of integrated antennas. Application of genetic algorithm to the optimization of.
A method for reducing the size of microstrip patch antennas by up to 75% by. Antenna theory and microstrip antennas electronic resource responsibility d. In the following sections a brief overview of all the algorithms are given followed by the verification of the results. The frequency of operation of the patch antenna of figure 1 is determined by the length l.
The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that is based on natural selection, the process that drives biological evolution. Genetic algorithm overview geneticalgorithm optimizers are robust, stochastic search methods, modeled on the principles and concepts of natural selec tion and evolution. A uniform array yields the smallest beamwidth and the highest directivity. However, rectangular patch antenna is more directive, it has 9 db in directivity and 61 in radiation beamwidth at eplane. Genetic algorithms belong to a stochastic class of evolutionary techniques, whose. A highdirectivity microstrip patch antenna design by using genetic. The optimization problem has three variables namely patch length, width and feed position respectively. However, in general the resulting beam patterns share a similar sidelobe level. Design and optimization of aperture coupled microstrip.
Elementary linear sources, including huygens planar element, and analysis and synthesis of the discrete and continuous arrays formed by these elementary sources the digital beamforming antenna and smart antenna cavity mode theory and. Analysis of the microstrip patch antenna designed using genetic. Introduction microstrip antenna, in its basic form, is a structure consists of a metallic radiating patch, etched on a dielectric substrate and backed by a ground plane. Genetic algorithm is a popular optimization technique and has been introduced for design optimization of proximity coupled antenna. Most practitioners use the genetic algorithm technique or some variant thereof to evolve antenna designs. As an optimizer, the powerful heuristic of the ga is effective at solving complex, combinatorial and related problems. The geometry obtained at the end of the genetic algorithm execution is shown in figure 4a. Return loss and radiation pattern for the optimized antenna are verified using ie3d software. Swastika slotted fractal antenna has been designed and fabricated by the use of fr4 substrate material which has 1. In real applications, the genetic algorithm is likely to be more. Genetic algorithm overview genetic algorithm optimizers are robust, stochastic search methods, modeled on the principles and concepts of natural selec tion and evolution. This book introduces the first step toward the implementation of the first new invented ghost radar at the world. In contrast, binomial arrays usually possess the smallest sidelobes fol. In this sense, this paper presents a novel patch antenna design with high directivity in the broadside direction by using genetic algorithms ga.
Tuning rectangular microstrip antenna through scan and. These types of antenna are used in low profile applications. In computer science and operations research, a genetic algorithm ga is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms ea. Directive antennas, genetic algorithms, linear antenna. The multiobjective feature allows the algorithm to be a. This paper presents an improved method of size reduction of a microstrip antenna using the genetic algorithm. Over roughly the same period, researchers at the illinois genetic algorithm laboratory illigal at the university of illinois at. Reasonable agreement between simulated results and measured results of the gaoptimized design is obtained. Ads platform is used for providing the lumped equivalent model analysis for designed antenna. Genetic algorithm and actual antenna array systems. Genetic algorithm ga is utilized to design microstrip patch antenna shapes for broad bandwidth. Haupt the pennsylvania state university applied research laboratory p. The first image shows a rectangular patch and its corresponding feedline. Genetic algorithm optimization for microstrip patch antenna miniaturization.
Good agreement is obtained between theoretical and experimental results. Evolutionary algorithms applied to antennas and propagation. Even though the content has been prepared keeping in mind the requirements of a beginner, the reader should be familiar with the fundamentals of programming and basic algorithms before starting with this tutorial. All these techniques are used for the feed point optimization of microstrip patch antenna. Determination of such design parameters has been made possible by utilising a multiobjective genetic algorithm mga approach. Abstract the application of genetic algorithm ga to the. A genetic algorithm ga is used to design patch shapes of microstrip antennas for multiband operations. Patch length, patch width are taken as optimization parameters. This procedure has been used in recent years to design a few antennas for missioncritical applications involving stringent, conflicting, or unusual design requirements, such as. Eas have emerged as viable candidates for global optimization problems and have been attracting the attention of the research community interested in solving realworld engineering problems, as evidenced by the fact that very large number of antenna design. The mission consists of three satellites that will take measurements in earths magnetosphere. Genetic algorithm optimization of broadband microstrip antenna.
Genetic algorithm for geometry optimization of optical. All the vital parameters like thickness of the substrate, bias magnetic field, length, width and dielectric constant etc. It is worth noting that the genetic algorithm does not always land on the same solution in each trial. Sierpinski bowtie antenna with genetic algorithm sciencedirect.
The genetic algorithm optimization gao is a promising method to overcome these limitations in antenna design 8 9101112. Radio telescopes can be built out of subarray and array patch antenna combinations for high resolution diffraction limit. Genetic algorithm ga, dual frequency, patch antenna, slot antenna. Ga optimization for rfid broadband antenna applications. A novel pattern of fractal antenna deploying swastika slotted geometry up to second iteration is used for optimization in this paper which enhanced its utilities for sband. In this paper, we utilize a genetic algorithm script in conjunction with a planar em simulator to perform novel pattern synthesis of a patch antenna. Keywordcircular patch antenna, directivity, genetic algorithm, hfss, rectangular patch antenna, return loss, triangular patch antenna.
The conditions for circular polarisation and impedance. Genetic algorithms and method of moments gamom for the. The design of a broadband patch antenna with greater than 20% bandwidth and a dualband patch antenna are presented as examples of the utility of gamom with dmm. This approach removes the requirement for quarterwave transformers associated with the conventional method, and. The antennas show the ability of the genetic algorithm to allow the designer to optimize an antenna for several different criteria at once, and to create new antennas with very little information from the designer other than general constraints and the desired performance characteristics. Genetic algorithm optimization for microstrip patch antenna. Conformal patch antenna arrays design for onboard ship.
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