Searching for convergence points of the continuous time extended Kalman filter used as a parameter estimator
- Resource Type
- Conference
- Authors
- Campbell, L.A.; Wiberg, D.M.
- Source
- [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on. :252-256 vol.1 1991
- Subject
- Signal Processing and Analysis
Computing and Processing
Differential equations
Parameter estimation
Riccati equations
State estimation
Ear
Stochastic systems
Filters
Convergence of numerical methods
Signal processing
Fluctuations
- Language
- ISSN
- 1058-6393
The authors deal with estimation of two stable pole parameters for a two-dimensional continuous-time linear stochastic system with known process noise covariance, using the extended Kalman filter. Averaging theory permits algebraic computation of a vector field whose stable stationary points are the estimator's only possible convergence points. Specialized partitioned matrix computations allow the numerical computation of the vector field and graphical computer search for spurious convergence points not corresponding to the true parameter values, with negative results. This supports the conjecture that none exist, a result known from theory in the one-dimensional case.ETX