{"title":"基于PSO的无源卫星TDOA和FDOA定位","authors":"Y. Bin, Qiu Yan, Lu An Nan","doi":"10.1109/ICIS.2011.47","DOIUrl":null,"url":null,"abstract":"Passive localization using TDOA and FDOA measurements usually does not have direct solution and requires numerical methods to determine the emitter's geolocation. We examine a satellite passive localization method based on particle swarm optimization(PSO), which provides an evolutionary computation method to solve the nonlinear optimal problem. However, PSO can not be straightforwardly applied to satellite passive localization because it is a constrained nonlinear optimal problem when using the constraint condition of the earth surface. We suggest \"flying\" the particle swarm directly using the earth surface constraint. Computer simulation results show the effectiveness of the new localization method.","PeriodicalId":256762,"journal":{"name":"2011 10th IEEE/ACIS International Conference on Computer and Information Science","volume":"193 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"PSO Based Passive Satellite Localization Using TDOA and FDOA Measurements\",\"authors\":\"Y. Bin, Qiu Yan, Lu An Nan\",\"doi\":\"10.1109/ICIS.2011.47\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Passive localization using TDOA and FDOA measurements usually does not have direct solution and requires numerical methods to determine the emitter's geolocation. We examine a satellite passive localization method based on particle swarm optimization(PSO), which provides an evolutionary computation method to solve the nonlinear optimal problem. However, PSO can not be straightforwardly applied to satellite passive localization because it is a constrained nonlinear optimal problem when using the constraint condition of the earth surface. We suggest \\\"flying\\\" the particle swarm directly using the earth surface constraint. Computer simulation results show the effectiveness of the new localization method.\",\"PeriodicalId\":256762,\"journal\":{\"name\":\"2011 10th IEEE/ACIS International Conference on Computer and Information Science\",\"volume\":\"193 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 10th IEEE/ACIS International Conference on Computer and Information Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIS.2011.47\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 10th IEEE/ACIS International Conference on Computer and Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIS.2011.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PSO Based Passive Satellite Localization Using TDOA and FDOA Measurements
Passive localization using TDOA and FDOA measurements usually does not have direct solution and requires numerical methods to determine the emitter's geolocation. We examine a satellite passive localization method based on particle swarm optimization(PSO), which provides an evolutionary computation method to solve the nonlinear optimal problem. However, PSO can not be straightforwardly applied to satellite passive localization because it is a constrained nonlinear optimal problem when using the constraint condition of the earth surface. We suggest "flying" the particle swarm directly using the earth surface constraint. Computer simulation results show the effectiveness of the new localization method.
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