基于RBPF的机动目标跟踪方法

2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2013-08-26 DOI:10.1109/IHMSC.2013.272

Xingxing Zou, Y. Zheng, Xiaomeng Zhang, Zengqiang Ma

{"title":"基于RBPF的机动目标跟踪方法","authors":"Xingxing Zou, Y. Zheng, Xiaomeng Zhang, Zengqiang Ma","doi":"10.1109/IHMSC.2013.272","DOIUrl":null,"url":null,"abstract":"The particle filtering (PF) is a widely used in present. However, as PF is used in nonlinear systems, a large number of particles are necessary to maintain high tracking accuracy and more computational burden are inevitably. Then, a new method of Rao-Blackwellised Particle (RBPF), in which Rao-Blackwell theorem is used to improve the performance of PF, is proposed in the paper. Firstly, nonlinear part and linear part of the maneuvering target tracking model are separated Based on Bayes principle. Then, the estimation of the linear part is dealed with by Kalman Filter (KF) and that of the nonlinear part by PF. The experiment results show that the tracking accuracy and the robustness of RBPF is higher than that of PF.","PeriodicalId":222375,"journal":{"name":"2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Maneuvering Target Tracking Method Based on RBPF\",\"authors\":\"Xingxing Zou, Y. Zheng, Xiaomeng Zhang, Zengqiang Ma\",\"doi\":\"10.1109/IHMSC.2013.272\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The particle filtering (PF) is a widely used in present. However, as PF is used in nonlinear systems, a large number of particles are necessary to maintain high tracking accuracy and more computational burden are inevitably. Then, a new method of Rao-Blackwellised Particle (RBPF), in which Rao-Blackwell theorem is used to improve the performance of PF, is proposed in the paper. Firstly, nonlinear part and linear part of the maneuvering target tracking model are separated Based on Bayes principle. Then, the estimation of the linear part is dealed with by Kalman Filter (KF) and that of the nonlinear part by PF. The experiment results show that the tracking accuracy and the robustness of RBPF is higher than that of PF.\",\"PeriodicalId\":222375,\"journal\":{\"name\":\"2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHMSC.2013.272\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2013.272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

粒子滤波(PF)是目前应用广泛的一种滤波技术。然而，在非线性系统中使用PF时，为了保持较高的跟踪精度，需要使用大量的粒子，从而不可避免地增加了计算量。在此基础上，提出了一种利用Rao-Blackwell定理提高粒子性能的Rao-Blackwell化粒子(RBPF)方法。首先，基于贝叶斯原理对机动目标跟踪模型的非线性部分和线性部分进行分离;然后用卡尔曼滤波(KF)对线性部分进行估计，用PF对非线性部分进行估计，实验结果表明，RBPF的跟踪精度和鲁棒性都高于PF。

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

A Maneuvering Target Tracking Method Based on RBPF

The particle filtering (PF) is a widely used in present. However, as PF is used in nonlinear systems, a large number of particles are necessary to maintain high tracking accuracy and more computational burden are inevitably. Then, a new method of Rao-Blackwellised Particle (RBPF), in which Rao-Blackwell theorem is used to improve the performance of PF, is proposed in the paper. Firstly, nonlinear part and linear part of the maneuvering target tracking model are separated Based on Bayes principle. Then, the estimation of the linear part is dealed with by Kalman Filter (KF) and that of the nonlinear part by PF. The experiment results show that the tracking accuracy and the robustness of RBPF is higher than that of PF.

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

2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics

自引率

0.00%

发文量