Rauch-Tung-Striebel高度培养卡尔曼平滑

Bin Jia, M. Xin
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引用次数: 2

摘要

本文提出了一种新的基于一类高次稳态规则的Rauch-Tung-Striebel型非线性平滑方法。这种高次培养卡尔曼平滑对传统的三次培养卡尔曼平滑进行了推广,大大提高了其估计精度。利用目标跟踪问题验证了该平滑器的性能,并将其与其他高斯逼近平滑器进行了比较。高次立方卡尔曼平滑优于扩展卡尔曼平滑、无气味卡尔曼平滑和三次立方卡尔曼平滑,并保持接近高斯-埃尔米特正交平滑的性能,且计算成本更低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rauch-Tung-Striebel high-degree cubature Kalman smoother
In this paper, a new Rauch-Tung-Striebel type of nonlinear smoothing method is proposed based on a class of high-degree cubature rules. This high-degree cubature Kalman smoother generalizes the conventional third-degree cubature Kalman smoother and considerably improves its estimation accuracy. A target tracking problem is utilized to demonstrate the performance of this new smoother and compare it with other Gaussian approximation smoothers. It will be shown that the high-degree cubabure Kalman smoother outperforms the extended Kalman smoother, the unscented Kalman smoother, the third-degree cubature Kalman smoother, and maintains close performance to the Gauss-Hermite quadrature smoother with much less computational cost.
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