The Interacting Multiple Model Filter on Boxplus-Manifolds
The Interacting Multiple Model Filter on Boxplus-Manifolds
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DOI：
10.1109/mfi49285.2020.9235232
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
Tom L. Koller;U. Frese
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文献类型：
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作者：
Tom L. Koller;U. Frese
交互多模型滤波器是状态估计的标准，其中需要不同的动态模型来对系统的行为进行建模。它执行估计的概率混合。到目前为止，如何在流形空间(如四元数)上正确地进行这种混合还没有定义。基于Boxplus方法，我们给出了可微流形上的适当概率混合。其结果是Boxplus流形上的交互多模型滤子。我们证明了我们的方法是最优解的一阶正确近似。该方法在模拟中进行了评估，并与四元数的自组织解决方案一样好。本文还给出了可微流形的Boxplus交互多模型滤波器的一般实现。
The interacting multiple model filter is the standard in state estimation where different dynamic models are required to model the behavior of a system. It performs a probabilistic mixing of estimates. Up to now, it is undefined how to perform this mixing properly on manifold spaces, e.g. quaternions. We present the proper probabilistic mixing on differentiable manifolds based on the boxplus-method. The result is the interacting multiple model filter on boxplus-manifolds. We prove that our approach is a first order correct approximation of the optimum. The approach is evaluated in a simulation and performs as good as the ad-hoc solution for quaternions. A generic implementation of the boxplus interacting multiple model filter for differentiable manifolds is published alongside with this paper.