基于联合概率数据关联滤波器的变数量目标跟踪

2016 24th Signal Processing and Communication Application Conference (SIU) Pub Date : 2016-06-23 DOI:10.1109/SIU.2016.7496165

Ahmet Cakiroglu

{"title":"基于联合概率数据关联滤波器的变数量目标跟踪","authors":"Ahmet Cakiroglu","doi":"10.1109/SIU.2016.7496165","DOIUrl":null,"url":null,"abstract":"Joint Probabilistic Data Association Filter (JPDAF) is an algorithm for overcoming the measurement-to-track association problem in multi-target tracking systems. JPDAF requires that the number of targets being tracked is a foreknown, constant parameter. Therefore, targets exiting and entering into the field of view reduces the tracking performance of JPDAF. In this work, an algorithm which makes it possible to use JPDAF for tracking variable number of targets is presented.","PeriodicalId":427250,"journal":{"name":"2016 24th Signal Processing and Communication Application Conference (SIU)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Tracking variable number of targets with Joint Probabilistic Data Association Filter\",\"authors\":\"Ahmet Cakiroglu\",\"doi\":\"10.1109/SIU.2016.7496165\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Joint Probabilistic Data Association Filter (JPDAF) is an algorithm for overcoming the measurement-to-track association problem in multi-target tracking systems. JPDAF requires that the number of targets being tracked is a foreknown, constant parameter. Therefore, targets exiting and entering into the field of view reduces the tracking performance of JPDAF. In this work, an algorithm which makes it possible to use JPDAF for tracking variable number of targets is presented.\",\"PeriodicalId\":427250,\"journal\":{\"name\":\"2016 24th Signal Processing and Communication Application Conference (SIU)\",\"volume\":\"2015 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 24th Signal Processing and Communication Application Conference (SIU)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2016.7496165\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 24th Signal Processing and Communication Application Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2016.7496165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 5

摘要

联合概率数据关联滤波(JPDAF)是一种克服多目标跟踪系统中测量-跟踪关联问题的算法。JPDAF要求跟踪的目标数量是一个已知的常数参数。因此，目标退出和进入视场降低了JPDAF的跟踪性能。本文提出了一种利用JPDAF跟踪变数量目标的算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Tracking variable number of targets with Joint Probabilistic Data Association Filter

Joint Probabilistic Data Association Filter (JPDAF) is an algorithm for overcoming the measurement-to-track association problem in multi-target tracking systems. JPDAF requires that the number of targets being tracked is a foreknown, constant parameter. Therefore, targets exiting and entering into the field of view reduces the tracking performance of JPDAF. In this work, an algorithm which makes it possible to use JPDAF for tracking variable number of targets is presented.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2016 24th Signal Processing and Communication Application Conference (SIU)

自引率

0.00%

发文量