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Estimated Time of Arrival Sensitivity to Aircraft Intent Uncertainty ?

机译：飞机意图不确定性的预计到达时间 ？

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摘要

Aircraft trajectory prediction is a feature at the core of most Air Traffic Management (ATM) applications. This process is strongly affected by stochastic sources that impact the accuracy of the predictions. The work presented hereafter focuses on application of the Polynomial Chaos theory to the quantification of the estimated time of arrival at designated waypoints throughout the trajectory. This methodology returns very accurate polynomial representations of trajectory uncertainties with very low computational requirements. This highly efficient approach enables the capability of quantifying the trajectory prediction uncertainties of a real traffic sample (i.e., thousands of flights) within seconds, which is fully compliant with the requirements of future advanced automation tools envisioned in future Trajectory Based Operations (TBO) environment.
机译：飞机轨迹预测是大多数空中交通管理（ATM）应用程序的核心功能。此过程受到随机源的强烈影响，这些随机源会影响预测的准确性。此后呈现的工作着重于将多项式混沌理论应用于量化在整个轨迹上到达指定航路点的估计到达时间。该方法以非常低的计算要求返回轨迹不确定性的非常精确的多项式表示形式。这种高效的方法能够在几秒钟内量化真实交通样本（即数千个航班）的轨迹预测不确定性，完全符合未来基于轨迹的运营（TBO）环境中设想的未来高级自动化工具的要求。

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