{"title":"A distributed object-oriented multi-mission radar waveform design implementation","authors":"V. Amuso, Brent Josefiak","doi":"10.1109/WDD.2012.7311254","DOIUrl":null,"url":null,"abstract":"This paper furthers the development of Genetic Algorithms (GAs) and their application to the design of multi-mission radar waveforms. An application was developed with the goal of developing a waveform suite that finds the Pareto optimal solutions to a multi-objective optimization radar problem. Utilizing the Strength Pareto Evolutionary Algorithm 2 (SPEA2) a series of radar parameters are optimized along the fitness metrics of interest. This implementation builds upon the previous work of [1] to develop an application that is capable of analyzing longer more realistic scenarios. It also advances the previous research by solving for the Pareto optimal front of a simultaneous Synthetic Aperture Radar (SAR) and Moving Target Indication (MTI) mission. These preliminary results are presented to validate the performance of the new application against previous work and introduce some results of the multi-mission radar suite.","PeriodicalId":102625,"journal":{"name":"2012 International Waveform Diversity & Design Conference (WDD)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Waveform Diversity & Design Conference (WDD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WDD.2012.7311254","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper furthers the development of Genetic Algorithms (GAs) and their application to the design of multi-mission radar waveforms. An application was developed with the goal of developing a waveform suite that finds the Pareto optimal solutions to a multi-objective optimization radar problem. Utilizing the Strength Pareto Evolutionary Algorithm 2 (SPEA2) a series of radar parameters are optimized along the fitness metrics of interest. This implementation builds upon the previous work of [1] to develop an application that is capable of analyzing longer more realistic scenarios. It also advances the previous research by solving for the Pareto optimal front of a simultaneous Synthetic Aperture Radar (SAR) and Moving Target Indication (MTI) mission. These preliminary results are presented to validate the performance of the new application against previous work and introduce some results of the multi-mission radar suite.