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Three examples of the stability properties of the invariant extended Kalman filter * * This work is supported by the company Safran.

机译:不变扩展卡尔曼滤波器的稳定性属性的三个示例 * < ce:footnote id =“ fn1”> * 赛峰公司支持这项工作。

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In the aerospace industry the (multiplicative) extended Kalman filter (EKF) is the most common method for sensor fusion for guidance and navigation. However, from a theoretical point of view, the EKF has been shown to possess local convergence properties only under restrictive assumptions. In a recent paper, we proved a slight variant of the EKF, namely the invariant extended Kalman filter (IEKF), when used as a nonlinear observer , possesses local convergence properties under the same assumptions as those of the linear case, for a class of systems defined on Lie groups. This is especially interesting as the IEKF also retains all the desirable features of the standard EKF, especially its relevant tuning in the presence of noises. In the present paper we provide three examples of engineering interest where the theory is shown to apply, yielding three EKF-like algorithms with guaranteed local convergence properties. Beyond those contributions, the present article is sufficiently accessible to help the practitioner understand through concrete examples the general IEKF theory, and to provide him with guidelines for the design of IEKFs.
机译:在航空航天工业中,(乘性)扩展卡尔曼滤波器(EKF)是用于引导和导航的传感器融合的最常用方法。然而,从理论上讲,仅在限制性假设下,EKF被证明具有局部收敛性。在最近的一篇论文中,我们证明了EKF的一个细微变化,即不变扩展卡尔曼滤波器(IEKF)在用作非线性观测器时,在与线性情况相同的假设下,具有一类局部线性收敛性。 Lie组上定义的系统。这尤其有趣,因为IEKF还保留了标准EKF的所有所需功能,尤其是在存在噪声的情况下进行相关调整。在本文中,我们提供了三个在工程上有意义的示例,这些示例显示了该理论的适用性,从而产生了三种具有保证局部收敛性的类EKF算法。除了这些贡献之外,本文还可以访问许多内容,以帮助从业人员通过具体实例了解IEKF的一般理论,并为IEKF的设计提供指导。

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