一种新型变增益无嗅卡尔曼滤波器及其在组合导航系统中的应用

Limin Zhang, Zengqiang Chen, Xinghui Zhang
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引用次数: 0

摘要

无气味卡尔曼滤波器是非线性系统中应用广泛的一种非线性滤波器。但由于系统建模的不准确性等原因,当扰动或观测异常出现时,UKF滤波算法不具备跟踪系统突变状态的能力,系统很可能变得不稳定。本文首先分析了UKF产生这些问题的原因,并对其进行了改进。然后,对无气味变换进行了详细的介绍,根据强跟踪滤波器的理论,提出了一种新的变增益无气味卡尔曼滤波器。最后,通过仿真实验对变增益UKF滤波器与标准UKF滤波器进行了比较。结果表明,变增益UKF具有在扰动或观测异常出现时跟踪系统突变状态的能力,使系统具有更好的鲁棒性和稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel varible gain unscented kalman filter and its application in the integrated navigation system
The unscented Kalman filter is a widely used nonlinear filter in nonlinear system. But because of inaccuracies of system modeling and other reasons, when the disturbance or observation anomaly appears, UKF filtering algorithm does not have the ability of tracking the mutation state of system, so the system is likely to become unstable. In this paper, the reasons for cause these problems of UKF are analysed firstly, and then, some improvements are made to it. Then, this paper gives a detailed introduction of unscented transform, according the theory of strong tracking filter, puts forward a new kind of variable gain unscented Kalman filter. At last, this paper does some simulation experiment to compare variable gain UKF filter with standard UKF. The results show that the variable gain UKF has the ability of tracking the mutation state of system when the disturbance or observation anomaly appears, and variable gain UKF really makes the system more robust and stable.
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