基于RFS的多目标跟踪信度空间及其与MHT的关系
A Belief Space Perspective of RFS based Multi-Target Tracking and its Relationship to MHT
摘要：
在本文中，我们建立了一个连接之间的Reid的HOMHT和现代的随机有限集（RFS）/有限集统计（FISST）为基础的多目标跟踪方法。我们从多目标概率密度函数（MT-pdf）的RFS描述开始，从置信空间的角度推导出RFS框架中MT跟踪问题的预测和更新方程。我们发现，RFS PDF有一个假设依赖的结构，这是类似的HOMHT假设结构。特别地，我们研究了不同的假设，推导了FISST递推下的假设更新公式，并清晰地展示了它与经典HOMHT假设和假设权值更新公式的关系，从而建立了方法之间的联系。
英文摘要：
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.
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