@inproceedings{09355fba03de4de18c7957c881e00b81,
title = "Non-material state estimation of arresting cable based on ALE formulation and UKF",
abstract = "This paper considers the problem that a sensor cannot directly obtain the arresting point status information of the arresting cable during the shipborne Unmanned Aerial Vehicle (UAV) cable-hock recovery process. To overcome this consideration, this study proposes an observation method based on Arbitrary Lagrangian Eulerian (ALE) formulation and Unscented Kalman Filter (UKF) for the non-material point status of the moving arresting cable. Specifically, the ALE method is used to model the dynamics of the arresting cable. Besides, the traditional Kalman filtering algorithm is employed, and the backward difference method is combined with UKF to estimate the vertical displacement of the arresting point on the arresting cable. Extensive simulations demonstrate that the proposed method accurately estimates the dynamic parameters of the arresting point in the arresting cable and achieves accurate state estimation of the carrier-based UAV recovery arresting cable.",
keywords = "Arbitrary Lagrangian Eulerian, State estimation, Unscented Kalman Filter, non-material point",
author = "Haiming Lei and Huan Zhang and Yue Hou and Tianci Zhang and Zhiquan Kong",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; 4th International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2023 ; Conference date: 10-03-2023 Through 12-03-2023",
year = "2023",
doi = "10.1117/12.2684928",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Fushuan Wen and Chuanjun Zhao and Yanjiao Chen",
booktitle = "Fourth International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2023",
address = "United States",
}