Jiang ZhengWang, L. Yinya, Mao Mingxiu, Chen Li, Guo Zhi
{"title":"多目标跟踪的改进概率数据关联算法研究","authors":"Jiang ZhengWang, L. Yinya, Mao Mingxiu, Chen Li, Guo Zhi","doi":"10.1109/CCDC.2009.5194908","DOIUrl":null,"url":null,"abstract":"An improved probabilistic data association is proposed to overcome both the drawback of complication in joint probabilistic data association and the unneutrality of multi-targets processing by probabilistic data association. It incorporates the radar Doppler measurement information and modifies weighting of state estimation of measurements in the common region, and then makes the final estimation more exact and improves further performance. The theoretical analysis and Monte-Carlo simulation results show that the algorithm has small computation cost and a better real-time tracking performance.","PeriodicalId":127110,"journal":{"name":"2009 Chinese Control and Decision Conference","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research of improved probability data association algorithm for multi-target tracking\",\"authors\":\"Jiang ZhengWang, L. Yinya, Mao Mingxiu, Chen Li, Guo Zhi\",\"doi\":\"10.1109/CCDC.2009.5194908\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improved probabilistic data association is proposed to overcome both the drawback of complication in joint probabilistic data association and the unneutrality of multi-targets processing by probabilistic data association. It incorporates the radar Doppler measurement information and modifies weighting of state estimation of measurements in the common region, and then makes the final estimation more exact and improves further performance. The theoretical analysis and Monte-Carlo simulation results show that the algorithm has small computation cost and a better real-time tracking performance.\",\"PeriodicalId\":127110,\"journal\":{\"name\":\"2009 Chinese Control and Decision Conference\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Chinese Control and Decision Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2009.5194908\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Chinese Control and Decision Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2009.5194908","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research of improved probability data association algorithm for multi-target tracking
An improved probabilistic data association is proposed to overcome both the drawback of complication in joint probabilistic data association and the unneutrality of multi-targets processing by probabilistic data association. It incorporates the radar Doppler measurement information and modifies weighting of state estimation of measurements in the common region, and then makes the final estimation more exact and improves further performance. The theoretical analysis and Monte-Carlo simulation results show that the algorithm has small computation cost and a better real-time tracking performance.
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