Estimating time-varying parameters by the Kalman filter based algorithm: stability and convergence

Guo L.

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Estimating time-varying parameters by the Kalman filter based algorithm: stability and convergence

机译：通过基于卡尔曼滤波器的算法估算时变参数：稳定性和收敛性

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Convergence and stability properties of the Kalman filter-based parameter estimator are established for linear stochastic time-varying regression models. The main features are: both the variances and sample path averages of the parameter tracking error are shown to be bounded; the regression vector includes both stochastic and deterministic signals, and no assumptions of stationarity or independence are requires; and the unknown parameters are only assumed to have bounded variations in an average sense.

机译：建立了基于卡尔曼滤波器的参数估计器的收敛性和稳定性，用于线性随机时变回归模型。主要特征是：参数跟踪误差的方差和样本路径平均值均显示为有界；回归向量包括随机和确定性信号，不需要平稳性或独立性的假设；而未知参数仅假设具有平均意义上的有界变化。

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《IEEE Transactions on Automatic Control》 |1990年第2期|P.141-147|共7页
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Guo L.;
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2. A time-varying forgetting factor stochastic gradient combined with Kalman filter algorithm for parameter identification of dynamic systems [J] . Junpeng Li, Changchun Hua, Yinggan Tang, Nonlinear dynamics . 2014,第3期

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3. Joint state and multi-innovation parameter estimation for time-delay linear systems and its convergence based on the Kalman filtering [J] . Ding Feng, Wang Xuehai, Mao Li, Digital Signal Processing . 2017,第期

机译：基于Kalman滤波的时延线性系统的联合状态和多创新参数估计及其收敛
4. Combining Kalman Filter and RLS-Algorithm to Improve a Textile based Sensor System in the Presence of Linear Time-Varying Parameters [C] . Manuel Schimmack, Paolo Mercorelli, Milan Maiwald International Conference on E-health Networking, Application Services . 2015

机译：结合卡尔曼滤波器和RLS算法在存在线性时变参数的情况下改进基于纺织传感器系统
5. Tracking and estimating dynamic magnetoencephalography (MEG) dipole source based on nonlinear Kalman Filters. [D] . Yao, Yuchen. 2010

机译：基于非线性卡尔曼滤波器的跟踪和估计动态磁脑电图（MEG）偶极子源。
6. An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking [O] . Wei Zhu, Wei Wang, Gannan Yuan 2016

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7. A Square-Root Second-Order Extended Kalman Filtering Approach for Estimating Smoothly Time-Varying Parameters [O] . Zachary F. Fisher, Sy-Miin Chow, Peter C. M. Molenaar, 2020

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8. Kalman Filter-Based Algorithms for Estimating Depth from Image Sequences [R] . Matthies, L., Szeliski, R., Kanade, T. 1988

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Estimating time-varying parameters by the Kalman filter based algorithm: stability and convergence

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