Improvement of UKF Algorithm and Robustness Study

Zhongkai Mou, L. Sui
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引用次数: 3

Abstract

Iterated unscented Kalman filter (IUKF) algorithm has improved the unscented Kalman filter (UKF) and enhanced the performance of filter estimation by using Newton-Raphson iterative equation. This paper improves IUKF algorithm ulteriorly after detailedly analyzing principle of IUKF and its iterative equation, and proposes a new filtering algorithm with robustness-Improved IUKF. Then the performance of the new algorithm is validated by two experiments. The results show that the improved IUKF is more robust which can effectively resist the influence of measurement outlier.
UKF算法改进及鲁棒性研究
迭代无气味卡尔曼滤波器(IUKF)算法是对无气味卡尔曼滤波器(UKF)的改进,利用牛顿-拉夫森迭代方程提高了滤波器估计的性能。本文在详细分析了IUKF的原理及其迭代方程的基础上,对IUKF算法进行了进一步改进,提出了一种新的具有鲁棒性的滤波算法——改进的IUKF。然后通过两个实验验证了新算法的性能。结果表明,改进后的IUKF具有更强的鲁棒性,能够有效抵抗测量异常值的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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