论文标题
基于RFS的多目标跟踪及其与MHT的关系的信念空间观点
A Belief Space Perspective of RFS based Multi-Target Tracking and its Relationship to MHT
论文作者
论文摘要
在本文中，我们建立了REID {'} S HOMHT与基于多目标跟踪的基于现代的随机有限集（RFS）/有限集统计（FISST）方法之间的联系。我们从对多目标概率密度函数（MT-PDF）的RFS描述开始，并从信念空间的角度来得出RFS框架中MT跟踪问题的预测和更新方程。我们表明，RFS PDF具有与HOMHT假设结构相似的假设依赖性结构。特别是，我们研究了不同的假设，并得出了Fisst递归下的假设更新方程，并清楚地显示了其与经典HOMHT假设和假设权重更新公式的关系，从而在方法之间建立了联系。
In this paper, we establish a connection between Reid{'}s HOMHT and the modern Random Finite Set (RFS)/ Finite Set Statistics (FISST) based methods for Multi-Target Tracking. We start with an RFS description of the Multi-Target probability density function (MT-pdf), and derive the prediction, and update equations of the MT-tracking problem in the RFS framework from a belief space perspective. We show that the RFS pdf has a hypothesis dependent structure that is similar to the HOMHT hypotheses structure. In particular, we examine the different hypotheses, and derive the hypotheses update equations under the FISST recursions, and clearly show its relationship to the classical HOMHT hypotheses and hypothesis weight update formula, thereby establishing a connection between the methods.
