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Multiple Frame Cluster Tracking

机译:多帧集群跟踪

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摘要

Tracking large number of closely spaced objects is a challenging problem for any tracking system. In missile defense systems, countermeasures in the form of debris, chaff, spent fuel, and balloons can overwhelm tracking systems that track only individual objects. Thus, tracking these groups or clusters of objects followed by transitions to individual object tracking (if and when individual objects separate from the groups) is a necessary capability for a robust and real-time tracking system. The objectives of this paper are to describe the group tracking problem in the context of multiple frame target tracking and to formulate a general assignment problem for the multiple frame cluster/group tracking problem. The proposed approach forms multiple clustering hypotheses on each frame of data and base individual frame clustering decisions on the information from multiple frames of data in much the same way that MFA or MHT work for individual object tracking. The formulation of the assignment problem for resolved object tracking and candidate clustering methods for use in multiple frame cluster tracking are briefly reviewed. Then, three different formulations are presented for the combination of multiple clustering hypotheses on each frame of data and the multiple frame assignments of clusters between frames.
机译:对于任何跟踪系统而言,跟踪大量紧密间隔的物体都是一个具有挑战性的问题。在导弹防御系统中,碎片,谷壳,乏燃料和气球等形式的对策会淹没仅跟踪单个物体的跟踪系统。因此,跟踪这些组或对象群集,然后过渡到单个对象跟踪(如果以及何时将单个对象从组中分离出来),对于强大且实时的跟踪系统来说是必要的功能。本文的目的是在多帧目标跟踪的背景下描述组跟踪问题,并为多帧聚类/组跟踪问题制定一般分配问题。所提出的方法在数据的每个帧上形成多个聚类假设,并以与MFA或MHT用于单个对象跟踪的方式几乎相同的方式,基于来自多个数据帧的信息进行单个帧聚类决策。简要回顾了用于解决的对象跟踪的分配问题的公式和用于多帧聚类跟踪的候选聚类方法。然后,针对数据的每个帧上的多个聚类假设以及帧之间的聚类的多个帧分配,提出了三种不同的表达方式。

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