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首页> 外文期刊>Mathematical Problems in Engineering >An IMM Filter Defined in the Linear-Circular Domain, Application to Maneuver Detection with Heading Only
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An IMM Filter Defined in the Linear-Circular Domain, Application to Maneuver Detection with Heading Only

机译：在线性圆域中定义的IMM滤波器，仅用于航向的机动检测

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摘要

In this article, we propose a multimodel filter for circular data. The so-called Circular Interacting Multimodel filter is derived in a Bayesian framework with the circular normal von Mises distribution. The aim of the proposed filter is to obtain the same performance in the circular domain as the classical IMM filter in the linear domain. In our approach, the mixing and fusion stages of the Circular Interacting Multimodel filter are, respectively, defined from the a priori and from the a posteriori circular distributions of the state angle knowing the measurements and according to a set of models. We propose in this article a set of circular models that will be used in order to detect the vehicle maneuvers from heading measurements. The Circular Interacting Multimodel filter performances are assessed on synthetic data and we show on real data a vehicle maneuver detection application.
机译：在本文中，我们提出了一种用于循环数据的多模型过滤器。在具有圆形正态冯·米塞斯分布的贝叶斯框架中推导了所谓的“循环交互多模型”滤波器。提出的滤波器的目的是在循环域中获得与经典IMM滤波器在线性域中相同的性能。在我们的方法中，圆形交互多模型滤波器的混合和融合阶段分别根据已知的测量值和一组模型从状态角的先验和后验圆形分布中定义。我们在本文中提出了一组圆形模型，这些模型将用于从航向测量中检测车辆操纵。循环交互多模型过滤器性能是根据综合数据评估的，我们在真实数据中显示了车辆操纵检测应用程序。

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