A New Look at Boundedness of Error Covariance of Kalman Filtering

A New Look at Boundedness of Error Covariance of Kalman Filtering
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卡尔曼滤波误差协方差有界性的新视角

DOI:
10.1109/tsmc.2016.2598845
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发表时间:
2018-02
影响因子:
8.7
通讯作者:
Alsaadi Fuad E.
Alsaadi Fuad E.
中科院分区:
计算机科学1区
文献类型:
--
作者:
Li Wangyan;Wei Guoliang;Ding Derui;Liu Yurong;Alsaadi Fuad E.

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在本文中,我们对卡尔曼滤波的误差协方差的有界性问题进行了新的研究。首先,利用数学归纳法,提出了一种新的依赖于系统参数的边界函数。这样,误差协方差的有界性问题就可以转化为对有界函数的一致有界性的研究。其次,基于这种有界函数,深入研究了误差协方差的动态性质、单调性和有界性问题。从而在极小条件下得到了误差协方差一致界的几个定量结果。最后,通过算例验证了理论分析的正确性和有效性。
In this correspondence paper, we provide a new look at the boundedness problems of error covariance of Kalman filtering. First, by utilizing the mathematical induction technique, a new bound function which is dependent on system parameters is proposed. In this manner, the boundedness problems of the error covariance can be converted to the study of the corresponding uniform bounds of the bound function. Second, based on such a bound function, the dynamic behaviors, monotonicities, and boundedness problems of error covariance are deeply explored. Consequently, a few quantitative results under minimal conditions about the uniform bounds on error covariance are obtained. Finally, examples are given to verify the correctness and effectiveness of our theoretical analyses.
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