摘要
群目标具有结构固定、运动模式特殊等特点,并且数量规模较大、空间分布密集、互相遮挡现象严重,采用传统的多目标跟踪算法对其进行跟踪会出现错误关联甚至失跟的现象。介绍了3种比较典型的群目标跟踪思路,即中心类跟踪算法、基于随机有限集的算法以及群扩展状态的估计算法,对目前的研究成果进行了分析和总结。最后,基于现有理论以及相近领域先进技术的发展,讨论了群目标跟踪的发展趋势。
Group targets have fixed structure, particular motion patterns, large quantity, dense spatial distribution and serious mutual occlusion. Traditional multi-target tracking algorithms may lead to wrong data association and even target loss. Three kinds of typical research ideas for group target tracking are introduced, including the centroid group tracking algorithm, the tracking algorithm based on the random finite set and the extended state tracking algorithm. Then, the research achievements at present are analyzed and summarized. Finally,based on the existing theory and the development of advanced technologies in similar research fields, the development trends of group target tracking are discussed.
作者
杜明洋
毕大平
王树亮
DU Ming-yang;BI Da-ping;WANG Shu-liang(College of Electronic Engineering,National University of Defense Technology,Hefei 230037,China)
出处
《电光与控制》
CSCD
北大核心
2019年第4期59-65,90,共8页
Electronics Optics & Control
基金
国家自然科学基金(61671453)
关键词
群目标
目标跟踪
群质心
随机有限集
扩展状态
group target
target tracking
centroid of group
random finite set
extended state
