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Filtering from observations on Stiefel manifolds

机译:从Stiefel流形上的观察中过滤

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This paper addresses the problem of filtering processes on the rotation group SO(n) when partial observations, i.e. processes on the Stiefel manifold, are only available. In particular, we consider the problem of estimating the angular velocity of an object when only partial observation of its orientation is available. Interpolation schemes are proposed to overcome the discrete nature of observations and a practical numerical solution (particle filtering) is developed for filtering on the Stiefel manifold. The proposed solution to the filtering problem is based on the anti-development signal concept, which allows to overcome the non-additivity nature of the noise present in the observed signal. The solutions proposed are general and can be transposed to many manifolds. However, the presented examples and simulations consider the case of partially observed signals taking values on the special orthogonal group when one or more components are missing. In this particular case, the observed process takes its values in the Stiefel manifold. A comparison of the proposed particle filter with the extended Kalman filter is presented. Results on synthetic and real (sport science) data show the behavior of the proposed algorithm.
机译:本文仅在部分观测(即Stiefel流形上的过程)可用时解决旋转组SO(n)上的滤波过程的问题。特别地,当仅部分观察对象的方位可用时,我们考虑估算对象的角速度的问题。提出了插值方案以克服观测值的离散性,并为在Stiefel流形上进行滤波开发了实用的数值解(粒子滤波)。所提出的滤波问题解决方案基于反展开信号概念,该概念可以克服所观察到的信号中存在的噪声的非可加性。提出的解决方案是通用的,可以转换为许多歧管。然而,当缺少一个或多个分量时,提出的示例和仿真考虑了部分观察到的信号在特殊正交组上取值的情况。在这种特定情况下,观察到的过程将在Stiefel流形中获取其值。提出的建议的粒子滤波器与扩展的卡尔曼滤波器的比较。综合和真实(体育科学)数据的结果表明了该算法的行为。

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