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Estimation of Maneuvering Aircraft States and Time-Varying Wind with Turbulence

机译:机动状态和随风时变风的估计

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摘要

This paper presents an application of the Square Root Unscented Kalman Filter (SR-UKF) to the estimation of aircraft system states and to the estimation of the total wind vector made up of a time-varying prevailing wind plus turbulence. The estimates are computed using conventional auto-pilot sensors with exponentially correlated measurement errors. The objective of this work is to investigate the convergence limitations of the estimates considering the covariance and time constants of the measurement error models as well as the level of intensity of the turbulence.
机译:本文介绍了平方根无味卡尔曼滤波器(SR-UKF)在飞机系统状态的估计以及由时变盛行风加湍流组成的总风矢量的估计中的应用。使用具有指数相关的测量误差的常规自动驾驶传感器来计算估计值。这项工作的目的是研究考虑到测量误差模型的协方差和时间常数以及湍流强度水平的估计的收敛性局限性。

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