Abstract
In this paper state and information space estimation methods used in both linear and nonlinear systems are compared. The (linear) information filter is introduced as an algebraic equivalent to the Kalman filter. Linear information space is extended to nonlinear information space by outlining the extended information filter. The algebraic equivalence of this filter to the extended Kalman filter and the benefits of nonlinear information space are illustrated by considering a system involving both nonlinear state evolution and nonlinear observations.
| Original language | English |
|---|---|
| Pages (from-to) | 2374-2375 |
| Number of pages | 2 |
| Journal | Proceedings of the American Control Conference |
| Volume | 4 |
| Publication status | Published - 1997 |
| Externally published | Yes |
| Event | Proceedings of the 1997 American Control Conference. Part 3 (of 6) - Albuquerque, NM, USA Duration: 4 Jun 1997 → 6 Jun 1997 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering