Abstract
The Kalman filtering algorithm is used to identify a class of signals imbedded in high amplitude measurement noise. The considered class of signals is first modeled empirically as a nonlinear equation. The equation is then linearized and formulated as a Kalman filtering state estimation problem. Computer simulations yield excellent results for a variety of examples, a couple of which are presented in this paper.
Original language | English (US) |
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Pages (from-to) | 995-1003 |
Number of pages | 9 |
Journal | Journal of the Franklin Institute |
Volume | 330 |
Issue number | 6 |
DOIs | |
State | Published - Nov 1993 |
Externally published | Yes |
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Computer Networks and Communications
- Applied Mathematics