| 基于随机集理论的多目标跟踪研究进展 |
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| 引用本文： | 陈金广,马丽丽.基于随机集理论的多目标跟踪研究进展[J].光电工程,2012,39(10):15-20. |
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| 作者姓名： | 陈金广 马丽丽 |
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| 作者单位： | 1. 西安工程大学计算机科学学院,西安710048;西安电子科技大学电子工程学院,西安710071
2. 西安工程大学计算机科学学院,西安,710048 |
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| 基金项目： | 国家自然科学基金项目 (61201118); 陕西省教育厅科研计划项目 (12JK0529); 西安工程大学博士科研启动基金 (BS1111) |
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| 摘 要： | 基于随机有限集理论的多目标跟踪方法,能够避免数据关联步骤的困扰,能够较好地解决复杂环境中目标数目未知且随时间变化的多目标跟踪问题.本文分析基于数据关联和基于随机集理论的多目标跟踪方法,阐明基于随机集理论的多目标跟踪方法的特点和优点,对目标状态提取、航迹关联、更准确的滤波算法,以及复杂条件下的PHDF算法等关键问题进行总结和评述,并指出该领域今后的研究热点.
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| 关 键 词： | 随机有限集 多目标跟踪 概率假设密度滤波 状态估计 粒子滤波 |
| 收稿时间： | 2012/5/10 |
Development of Multi-target Tracking Methods Based on Random Finite Set |
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| CHEN Jin-guang
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MA Li-li.Development of Multi-target Tracking Methods Based on Random Finite Set[J].Opto-Electronic Engineering,2012,39(10):15-20. |
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| Authors: | CHEN Jin-guang MA Li-li |
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| Affiliation: | 1(1.School of Computer Science,Xi’an Polytechnic University,Xi’an 710048,China;2.School of Electronic Engineering,Xidian University,Xi’an 710071,China) |
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| Abstract: | Multi-target tracking methods based on random finite set theory can avoid problems appeared in the progress of data association. It can also deal with multi-target tracking problems in the complex environment with target number unknown and target number varying with time. In this work, multi-target tracking methods based on data association and random finite set are analyzed. Characters and advantages of tracking methods based on random finite set are described. Some key problems, like target state extraction, track-to-track association, more accurate filtering algorithms, and PHDF algorithms under complex situations, are summarized and reviewed, and then some research focuses in the following years are given. |
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| Keywords: | random finite set multi-target tracking probability hypothesis density filter state estimation particle filter |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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