{"title":"多目标地面跟踪与道路地图和粒子过滤器","authors":"G. Kravaritis, B. Mulgrew","doi":"10.1109/ISSPIT.2005.1577104","DOIUrl":null,"url":null,"abstract":"This paper studies the problem of tracking multiple targets on the ground when information about the road map is available. It introduces an algorithmic structure which employs a particle filter for estimation and tracking in conjunction with a gating function and a data association scheme for measurement-to-track assignment. The proposed technique is based on the variable structure multiple model particle filter and the joint probabilistic data association algorithm","PeriodicalId":421826,"journal":{"name":"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Multitarget ground tracking with road maps and particle filters\",\"authors\":\"G. Kravaritis, B. Mulgrew\",\"doi\":\"10.1109/ISSPIT.2005.1577104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies the problem of tracking multiple targets on the ground when information about the road map is available. It introduces an algorithmic structure which employs a particle filter for estimation and tracking in conjunction with a gating function and a data association scheme for measurement-to-track assignment. The proposed technique is based on the variable structure multiple model particle filter and the joint probabilistic data association algorithm\",\"PeriodicalId\":421826,\"journal\":{\"name\":\"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPIT.2005.1577104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2005.1577104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multitarget ground tracking with road maps and particle filters
This paper studies the problem of tracking multiple targets on the ground when information about the road map is available. It introduces an algorithmic structure which employs a particle filter for estimation and tracking in conjunction with a gating function and a data association scheme for measurement-to-track assignment. The proposed technique is based on the variable structure multiple model particle filter and the joint probabilistic data association algorithm
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