仅使用高斯-埃尔米特滤波跟踪方位

G. Chalasani, S. Bhaumik
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引用次数: 29

摘要

本文从估计精度、失迹概率和计算效率三个方面,比较了高斯-赫米特滤波(GHF)在纯方位跟踪问题中的性能与扩展卡尔曼滤波(EKF)和无气味卡尔曼滤波(UKF)。与EKF和UKF相比,在初始不确定性较大的情况下,随着正交点的增加和鲁棒性的增强,GHF的性能得到了改善。结果表明,在不引入大量计算负担的情况下,具有三个或更多正交点的GHF比UKF和EKF表现出更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bearing only tracking using Gauss-Hermite filter
In this paper, performance of Gauss-Hermite filter (GHF) in bearing only tracking problem has been compared with that of extended Kalman filter (EKF) and unscented Kalman filter (UKF) in terms of estimation accuracy, probability of track-loss and computational efficiency. The performance improvement of the GHF with increase in quadrature points and enhanced robustness compared to EKF and UKF with respect to large initial uncertainty has been reported. It has been concluded that without introducing substantial computational burden, GHF with three or more quadrature points exhibits better performance compared to UKF and EKF.
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