Lp‐stability of estimation errors of kalman filter for tracking time‐varying parameters
- 1 May 1991
- journal article
- research article
- Published by Wiley in International Journal of Adaptive Control and Signal Processing
- Vol. 5 (3) , 155-174
- https://doi.org/10.1002/acs.4480050302
Abstract
The Kalman filtering algorithm, owing to its optimality in some sense, is widely used in systems and control, signal processing and many other fields. This paper presents a detailed analysis for theLp‐stability of tracking errors when the Kalman filter is used for tracking unknown time‐varying parameters. The results of this paper differ from the previous ones in that the regression vector (in a linear regression model) or the output matrix (in state space terminology) is random rather than deterministic. The context is kept general so that, in particular, the time‐varying parameter is allowed to be unbounded, and no assumption of stationarity or independence for signals is made.Keywords
This publication has 14 references indexed in Scilit:
- Estimating time-varying parameters by the Kalman filter based algorithm: stability and convergenceIEEE Transactions on Automatic Control, 1990
- On Kalman filtering for conditionally Gaussian systems with random matricesSystems & Control Letters, 1989
- Frequency domain tracking characteristics of adaptive algorithmsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1989
- The limiting behavior of LMSIEEE Transactions on Acoustics, Speech, and Signal Processing, 1989
- Design of adaptive algorithms for the tracking of time‐varying systemsInternational Journal of Adaptive Control and Signal Processing, 1987
- Optimization of adaptive identification for time-varying filtersIEEE Transactions on Automatic Control, 1986
- Tracking error bounds of adaptive nonstationary filteringAutomatica, 1985
- A measure of the tracking capability of recursive stochastic algorithms with constant gainsIEEE Transactions on Automatic Control, 1982
- PrefacePublished by Elsevier ,1970
- Local Convergence of Martingales and the Law of Large NumbersThe Annals of Mathematical Statistics, 1965