论文标题
PMBM贝叶斯轨道启动与标记的RFS自适应出生之间的比较
A comparison between PMBM Bayesian track initiation and labelled RFS adaptive birth
论文作者
论文摘要
本文提供了标记为随机有限套装文献中使用的自适应出生模型与带有点目标模型的Poisson Multi-Bernoulli混合物（PMBM）滤波器中使用的轨道启动之间的比较分析。 PMBM轨道的启动是通过对预测的PMBM密度应用的贝叶斯规则获得的，并为每个接收的测量值创建一个Bernoulli组件，表示该测量可能是杂乱无章的或从新目标中检测的。自适应出生模拟此过程，通过使用不同的规则为每个测量创建一个bernoulli组件，以确定存在的概率和用户定义的单目标密度。本文首先提供了基于孤立测量结果在轨道启动中产生的差异的分析。然后，它表明自适应出生低估了在共同建模假设下监视区域中存在的物体数量。最后，我们提供数值模拟，以进一步说明差异。
This paper provides a comparative analysis between the adaptive birth model used in the labelled random finite set literature and the track initiation in the Poisson multi-Bernoulli mixture (PMBM) filter, with point-target models. The PMBM track initiation is obtained via Bayes' rule applied on the predicted PMBM density, and creates one Bernoulli component for each received measurement, representing that this measurement may be clutter or a detection from a new target. Adaptive birth mimics this procedure by creating a Bernoulli component for each measurement using a different rule to determine the probability of existence and a user-defined single-target density. This paper first provides an analysis of the differences that arise in track initiation based on isolated measurements. Then, it shows that adaptive birth underestimates the number of objects present in the surveillance area under common modelling assumptions. Finally, we provide numerical simulations to further illustrate the differences.
