Abstract
A solution is provided to the problem of computing a convex set of conditional probability distributions that characterize the state of a nonlinear dynamic system as it evolves in time. The estimator uses the Galerkin approximation to solve Kolmogorov's equation for the diffusion of a continuous-time nonlinear system with discrete- time measurement updates. Fitering of the state is accomplished for a convex set of distributions simultaneously, and closed-form representations of the resulting sets of means and covariances are generated.
Keywords. nonlinear filtering, convex sets of distributions, set-valued estimation
The paper is available in the following formats:
Authors addresses:Electrical and Computer Engineering
E-mail addresses:
| John Kenney | keney@ee.byu.edu, wynn@ee.byu.edu |
| Wynn Stirling |