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A NON-LINEAR OBSERVER BASED INTEGRATED NAVIGATION ALGORITHM

机译:基于非线性观测器的集成导航算法

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摘要

The integrated navigation systems reduce the menial navigation system errors estimating them by means of an observer and additional sensors. These errors have nonlinear dynamics, thus the need for an nonlinear observer. Given the complexity of the nonlinear observer design, is common practice the use of the Extended Kalman Filter or one of its variants, which present the disadvantage of lacking results over their convergence. In this work a nonlinear hybrid observer is presented. Using attitude information obtained at discrete instants this observer estimate the attitude and gyroscopes' errors, achieving a higher inertial navigation precision in the absence of information from the additional sensors. Conditions are established for the global exponential convergence and robustness in presence of bounded perturbations.
机译:集成的导航系统减少了通过观察员和附加传感器估算的局部导航系统错误。这些误差具有非线性动力学,因此需要非线性观测器。考虑到非线性观测器设计的复杂性,通常的做法是使用扩展卡尔曼滤波器或其变体之一,这带来了缺点,即由于收敛而缺乏结果。在这项工作中,提出了一种非线性混合观测器。该观察者使用在离散时刻获得的姿态信息来估算姿态和陀螺仪的误差,从而在没有来自附加传感器的信息的情况下获得更高的惯性导航精度。在存在有限摄动的情况下,为全局指数收敛和鲁棒性建立了条件。

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