multi-objective optimization for antenna · pdf filemulti-objective optimization for antenna...

case history

network.modefrontier.eumodeFRONTIER® is a trademark of ESTECO srl, Italy

EnginSoft Promotes EuropeanmodeFRONTIER Network

Multi-objective optimization

for antenna design

The problem described here concerns the optimization of a sevenelement antenna with the purpose to improve its radiatingperformance.

The aim of this work is to test the effectiveness of native, truemulti-objective optimization techniques, available today inmodeFRONTIER®4, a ready-to-use multi-objective environ-ment, directly driving CST MWS, thus taking advantage of someuseful interactive postprocessing tools.

The model is a representative element of an L band feed arraywhich is actually a part of an unfurlable array fed reflectorantenna typically used for Mobile Satellite Services.In the optimization of the feed element we have changed thegeometrical parameters of the input section, including thecavity and patch dimensions, and the position of the patchwithin the cavity.

In this study, we considered eight geometric parameters.It was decided to set 3 different objectives:1. Minimization of the Return Loss for each of the two ports;2. Minimization of the electromagnetic coupling between ports;3. Minimization of the cross polarization component.

CST MICROWAVE STUDIO® (CST MWS) is a tool for the simulationof high frequency (HF) devices such as antennas, filters,couplers, planar and multi-layer structures and SI and EMCeffects. Besides the time domain simulator, which usesproprietary PERFECT BOUNDARY APPROXIMATION (PBA®)

technology, CST MWS offers frequency domain on hexahedraland tetrahedral meshes, an Integral Equation solver for largestructures, and a fast sparameter solver dedicated to highlyresonant structures.

Multi-objective means a given number of functions have to besimultaneously maximized or minimized.Hence, in multi-objective optimization, the concept of bestdesign is replaced by the concept of dominant design.Pareto dominance:

Problem Description

Model,Parametrization,Strategies andTargets

Numerical techniques used in the 3D EM CST MWS codeemployed

Multi-objective Optimization concepts and ParetoFrontier

case history

network.modefrontier.eumodeFRONTIER® is a trademark of ESTECO srl, Italy

EnginSoft Promotes EuropeanmodeFRONTIER Network

Optimization Setup

Chosen Optimization strategy:MOGT & MOGA-II

Conclusions

Before running the optimization the antenna model isintegrated in the selected optimization environment,modeFRONTIER®4.Every single design configuration is evaluated in batch mode inorder to let the optimizer work without human intervention andfully exploit the advantages of the optimization algorithms.Since the optimization tool provides a direct interface to the CSTMICROWAVE STUDIO® model, the optimization variables aredirectly linked to the antenna parameters and the analysisresults are extracted and linked to the optimization targets.

Since the response of the system to the modifications of the freeparameters is unknown, a twophase optimization is carried out.

In the first phase, the Multi-Objective Game Theory (MOGT) isused in order to have a fast mapping of the three dimensionalPareto frontier.In the second phase, a Multi-Objective Genetic Algorithm(MOGA II) refines the Pareto frontier exploration starting fromsome selected points of the firstoptimization run.

• Once the integration of the model in the optimizationenvironment is done, all the optimization capabilities canbe applied to improve the performance of the antenna.

• The optimization is a full batch process.• Today's multi-core PCs and clusters are able to carry out

multi-objective optimization of a complex model inreasonable computational time.

For more information:M. Poian - ESTECOpoian@esteco.com

S. Poles - ESTECOpoles@esteco.com

E. Leroux - CST GmbHemmanuel.leroux@cst.com

W. Steffé - Thales Alenia Spacewalter.steffe@thalesaleniaspace.com

M. Zolesi - Thales Alenia Spacemarcello.zolesi@thalesaleniaspace.com