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Convergence of discrete-time Kalman filter estimate to continuous-time estimate for systems with unbounded observation

机译:具有无界观测的系统的离散时间Kalman滤波器估计到连续时间估计的收敛性

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摘要

In this article, we complement recent results on the convergence of the state estimate obtained by applying the discrete-time Kalman filter on a time-sampled continuous-time system. As the temporal discretization is refined, the estimate converges to the continuous-time estimate given by the Kalman–Bucy filter. We shall give bounds for the convergence rates for the variance of the discrepancy between these two estimates. The contribution of this article is to generalize the convergence results to systems with unbounded observation operators under different sets of assumptions, including systems with diagonaliz-able generators, systems with admissible observation operators, and systems with analytic semigroups. The proofs are based on applying the discrete-time Kalman filter on a dense, numerable subset on the time interval [0,T] and bounding the increments obtained. These bounds are obtained by studying the regularity of the underlying semigroup and the noise-free output.
机译:在本文中,我们对通过在时间采样连续时间系统上应用离散时间卡尔曼滤波器获得的状态估计的收敛性的最新结果进行补充。随着时间离散化的完善,估计收敛到由卡尔曼–布西滤波器给出的连续时间估计。对于这两个估计之间差异的方差,我们将给出收敛速度的界限。本文的作用是将收敛结果推广到不同假设条件下具有无界观测算子的系统,包括具有可对角线生成器的系统,具有可容许观测器的系统以及具有解析半群的系统。证明是基于在时间间隔[0,T]上将离散时间Kalman滤波器应用于密集,可数的子集并限制获得的增量。这些边界是通过研究基础半群和无噪声输出的规律性而获得的。

著录项

  • 作者

    Aalto, Atte;

  • 作者单位
  • 年度 2015
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类
  • 入库时间 2022-08-20 20:22:33

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