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The Enriched Sigma Point Kalman filter An adaptation of the Unscented Kalman Filter for navigation applications

机译:丰富的Sigma Point Kalman滤波器针对导航应用的Unscented Kalman滤波器的改编

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The Unscented Kalman Filter (UKF) has received a lot of attention in the last few years, especially for inertial navigation applications. Indeed, it efficiently extends the non-linear capacities of the Extended Kalman Filter (EKF), and provides additional benefits, such as an absence of divergence and a black-box implementation that simplifies the maintenance of such an algorithm. Nevertheless, during the heading determination phase of an inertial navigation algorithm, the barycentre of the unscented transform used to represent the system state is not adapted because it creates an artificial position error. An alternative algorithm, using a so-called ‘Central point’ allows to benefit from the UKF capabilities while suppressing this drawback, making it possible to determine the heading of a system without any of the static constraints of a traditional inertial navigation system.
机译:在过去的几年中,无味卡尔曼滤波器(UKF)受到了很多关注,特别是在惯性导航应用中。实际上,它有效地扩展了扩展卡尔曼滤波器(EKF)的非线性能力,并提供了其他好处,例如,没有分歧和简化了这种算法维护的黑匣子实现。但是,在惯性导航算法的航向确定阶段,用于表示系统状态的无味变换的重心不适应,因为它会产生人为的位置误差。使用所谓的“中心点”的另一种算法可以从UKF功能中受益,同时消除了这一缺陷,从而可以确定系统的航向而没有传统惯性导航系统的任何静态约束。

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