Júlio Cesar Eduardo de Souza, V. Prado, Ó. Martínez-Graullera, R. Higuti
{"title":"A New Fitness Function for Sparse Linear Array Evaluation Based on the Point Spread Function","authors":"Júlio Cesar Eduardo de Souza, V. Prado, Ó. Martínez-Graullera, R. Higuti","doi":"10.1109/LAUS53676.2021.9639116","DOIUrl":null,"url":null,"abstract":"This work proposes a new fitness function for sparse linear array design using the Point Spread Function (PSF), where the energy and entropy are combined. The Arithmetic optimization Algorithm is used as a search mechanism, and a new strategy to find sparse linear configurations is proposed. This new strategy eliminates the necessity of penalization functions to control the number of elements in sparse arrays. The algorithm is used to find two sparse linear arrays, one using a fitness function based on the radiation pattern, and the other with the proposed fitness function. Comparing the results, the configuration found using the proposed fitness function presented better lateral resolution and contrast.","PeriodicalId":156639,"journal":{"name":"2021 IEEE UFFC Latin America Ultrasonics Symposium (LAUS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE UFFC Latin America Ultrasonics Symposium (LAUS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LAUS53676.2021.9639116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work proposes a new fitness function for sparse linear array design using the Point Spread Function (PSF), where the energy and entropy are combined. The Arithmetic optimization Algorithm is used as a search mechanism, and a new strategy to find sparse linear configurations is proposed. This new strategy eliminates the necessity of penalization functions to control the number of elements in sparse arrays. The algorithm is used to find two sparse linear arrays, one using a fitness function based on the radiation pattern, and the other with the proposed fitness function. Comparing the results, the configuration found using the proposed fitness function presented better lateral resolution and contrast.