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arXiv 1603.04519math.OC
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角速度测量中存在偏差时的变姿态估计

The Variational Attitude Estimator in the Presence of Bias in Angular Velocity Measurements

Maziar Izadi, Sasi Prabhakaran Viswanathan, Amit Kumar Sanyal, Carlos Silvestre, Paulo Oliveira

摘要:

刚体姿态运动的估计是一个长期存在的问题,在一些应用中的利益。这个问题是具有挑战性的,主要是因为刚体运动是由非线性动力学和状态空间是非线性的。在过去的几十年里,扩展卡尔曼滤波器及其几种变体仍然是姿态估计的标准和最常用的方案。这些格式作为非线性最优滤波问题的近似解而得到。然而,这些近似或接近最优解的解通常不能给出稳定的估计方案。变分姿态估计器的引入填补了在初态不确定和测量噪声未知的情况下稳定估计任意刚体姿态运动的空白。该估计量是通过应用拉格朗日-达朗贝尔原理的变分力学的拉格朗日构造的测量和状态估计之间的残差与耗散项,是线性的角速度测量残差。在这项工作中,变分姿态估计广义包括角速度测量,除了测量噪声有一个恒定的偏差。状态估计在状态空间上几乎全局收敛于真实状态。此外,一旦状态估计收敛到真实状态,则偏差估计收敛到真实偏差。

英文摘要:

Estimation of rigid body attitude motion is a long-standing problem of interest in several applications. This problem is challenging primarily because rigid body motion is described by nonlinear dynamics and the state space is nonlinear. The extended Kalman filter and its several variants have remained the standard and most commonly used schemes for attitude estimation over the last several decades. These schemes are obtained as approximate solutions to the nonlinear optimal filtering problem. However, these approximate or near optimal solutions may not give stable estimation schemes in general. The variational attitude estimator was introduced recently to fill this gap in stable estimation of arbitrary rigid body attitude motion in the presence of uncertainties in initial state and unknown measurement noise. This estimator is obtained by applying the Lagrange-d'Alembert principle of variational mechanics to a Lagrangian constructed from residuals between measurements and state estimates with a dissipation term that is linear in the angular velocity measurement residual. In this work, the variational attitude estimator is generalized to include angular velocity measurements that have a constant bias in addition to measurement noise. The state estimates converge to true states almost globally over the state space. Further, the bias estimates converge to the true bias once the state estimates converge to the true states.

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