Design of measurement difference autocovariance method for estimation of process and measurement noise covariances
From MaRDI portal
Publication:1640708
DOI10.1016/j.automatica.2017.12.040zbMath1387.93151OpenAlexW2783465527MaRDI QIDQ1640708
Jindřich Duník, Ondřej Straka, Oliver Kost
Publication date: 14 June 2018
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.automatica.2017.12.040
Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12)
Related Items (5)
Point-Mass Filter: Density Specific Grid Design and Implementation ⋮ Extracting a low-dimensional predictable time series ⋮ Adaptive Kalman filtering for closed-loop systems based on the observation vector covariance ⋮ Predicting the output error of the suboptimal state estimator to improve the performance of the MPC-based artificial pancreas ⋮ Parameter estimation for a class of time‐varying systems with the invariant matrix
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
- Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters
- Stochastic models, estimation, and control. Vol. 2,3
- Estimation of the disturbance structure from data using semidefinite programming and optimal weighting
- Estimation of noise covariance matrices for a linear time-varying stochastic process
- Factorization methods for discrete sequential estimation
- A new autocovariance least-squares method for estimating noise covariances
- An online parameter estimator for quick convergence and time-varying linear systems
- On Autocovariance Least-Squares Method for Noise Covariance Matrices Estimation
- Estimation of noise covariance matrices for periodic systems
- An efficient algorithm for estimating noise covariances in distributed systems
- A direct approach to identify the noise covariances of Kalman filtering
- Adaptive sequential estimation with unknown noise statistics
- Kronecker products and matrix calculus in system theory
- Noise covariance matrices in state‐space models: A survey and comparison of estimation methods—Part I
- Kalman filtering with no a priori information about noise--White noise case: Identification of covariances
- A convergent approximation of the continuous-time optimal parameter estimator
- Approaches to adaptive filtering
This page was built for publication: Design of measurement difference autocovariance method for estimation of process and measurement noise covariances