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Kalman Filter Cascade for Attitude Estimation on Rotating Earth
IEEE/ASME Transactions on Mechatronics ( IF 6.4 ) Pub Date : 2019-12-11 , DOI: 10.1109/tmech.2019.2959080
Joel Reis , Pedro Batista , Paulo Oliveira , Carlos Silvestre

This article presents a discrete-time attitude estimation solution based on a cascade of two linear time-varying Kalman filters (KFs). Under mild assumptions, the cascade's first KF resorts to body-fixed measurements of angular velocity and of a constant inertial vector to yield an estimate of Earth's angular velocity. The latter, in addition to all previous measurements, is fed to the second KF to obtain an estimate of the rotation matrix. Although topological constructions are lifted, a last-step projection operator is employed that maps the final rotation matrix estimate onto SO(3). Briefly, two linear time-varying systems are designed, with no linearizations whatsoever, that are shown to be uniformly completely observable, thus rendering the overall solution globally exponentially stable. Simulation results are presented that allow to assess the performance of the cascaded KF duo. A set of experimental results is also presented that validates the efficiency of the proposed solution and deems it a suitable attitude estimation choice for applications where only one body-vector measurement is available.

中文翻译:

卡尔曼滤波器级联用于旋转地球上的姿态估计

本文提出了一种基于两个线性时变卡尔曼滤波器(KFs)的级联的离散时间姿态估计解决方案。在温和的假设下,级联的第一个KF求助于角速度和恒定惯性矢量的人体固定测量,以估算地球的角速度。除了所有先前的测量之外,后者被馈送到第二KF,以获得旋转矩阵的估计值。尽管取消了拓扑结构,但采用了最后一步的投影算子,将最终的旋转矩阵估计映射到SO(3)。简而言之,设计了两个线性时变系统,它们没有任何线性化,被证明可以完全完全观察到,从而使整体解决方案在全局范围内呈指数稳定。仿真结果可以评估级联KF二重奏的性能。还提供了一组实验结果,这些结果验证了所提出解决方案的效率,并认为它是仅可用于一个人体矢量测量的应用的合适姿态估计选择。
更新日期:2020-04-22
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