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A novel varible gain unscented kalman filter and its application in the integrated navigation system

机译:新型变增益无味卡尔曼滤波器及其在组合导航系统中的应用

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摘要

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.
机译:无味卡尔曼滤波器是非线性系统中广泛使用的非线性滤波器。但是由于系统建模的不准确等原因,当出现扰动或观测异常时,UKF滤波算法不具有跟踪系统突变状态的能力,因此系统可能会变得不稳定。本文首先分析了造成UKF问题的原因,然后对其进行了一些改进。然后,根据强跟踪滤波器的理论,对无味变换进行了详细的介绍,提出了一种新型的可变增益无味卡尔曼滤波器。最后,本文进行了仿真实验,比较了可变增益UKF滤波器和标准UKF滤波器。结果表明,当出现扰动或观测异常时,可变增益UKF能够跟踪系统的突变状态,可变增益UKF确实使系统更加健壮和稳定。

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