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Performance and stochastic stability of the adaptive fading extended Kalman filter with the matrix forgetting factor : Open Mathematics

机译:具有矩阵遗忘因子的自适应衰落扩展卡尔曼滤波器的性能和随机稳定性:开放数学

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摘要

In this paper, the stability of the adaptive fading extended Kalman filter with the matrix forgetting factor when applied to the state estimation problem with noise terms in the non–linear discrete–time stochastic systems has been analysed. The analysis is conducted in a similar manner to the standard extended Kalman filter’s stability analysis based on stochastic framework. The theoretical results show that under certain conditions on the initial estimation error and the noise terms, the estimation error remains bounded and the state estimation is stable.The importance of the theoretical results and the contribution to estimation performance of the adaptation method are demonstrated interactively with the standard extended Kalman filter in the simulation part.
机译:本文分析了在非线性离散时间随机系统中,带有矩阵遗忘因子的自适应衰落扩展卡尔曼滤波器的稳定性,适用于带有噪声项的状态估计问题。该分析与基于随机框架的标准扩展卡尔曼滤波器的稳定性分析类似。理论结果表明,在一定的初始估计误差和噪声项条件下,估计误差仍然是有界的,状态估计是稳定的。交互论证了理论结果的重要性和对自适应方法对估计性能的贡献。模拟部分中的标准扩展卡尔曼滤波器。

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