一个标记的随机有限集刷出模型

Daniel S. Bryant, B. Vo, B. Vo, B. Jones
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引用次数: 1

摘要

以前的标记随机有限集过滤器开发使用的目标运动模型只考虑生存和出生。虽然这种模型为多目标跟踪过滤器(如广义标记多伯努利过滤器)提供了在各种应用中捕获目标出生和死亡的手段,但它缺乏捕获生成目标轨迹的谱系的能力。在本文中,我们提出了一个标记的随机有限集生成模型,并推导了结果的多目标预测和过滤密度。这个公式允许对派生对象的状态和有关其沿袭的信息进行联合估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A labeled random finite set spawning model
Previous labeled random finite set filter developments use a target motion model that only accounts for survival and birth. While such a model provides the means for a multi-target tracking filter such as the Generalized Labeled Multi-Bernoulli filter to capture target births and deaths in a wide variety of applications, it lacks the capability to capture the lineages of spawned target tracks. In this paper, we propose a labeled random finite set spawning model and derive the resulting multi-target prediction and filtering densities. This formulation enables the joint estimation of spawned object's state and and information regarding its lineage.
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