A Tool for Kalman Filter Tuning
Publication: Research › Article in proceedings – Annual report year: 2007
The Kalman filter requires knowledge about the noise statistics. In practical
applications, however, the noise covariances are generally not known. A
method for estimating noise covariances from process data has been
investigated. The method gives a least-squares estimate of the noise
covariances, which can be used to compute the Kalman filter gain.
| Original language | English |
|---|---|
| Title | 17th European Symposium on Computer Aided Process Engineering - ESCAPE17, 2007 |
| Number of pages | 1392 |
| Volume | Volume 24 |
| Publisher | Elsevier |
| Publication date | 2007 |
| Pages | 859-864 |
| ISBN (print) | 978-0-444-53157-5 |
| DOIs | |
| State | Published |
Conference
| Conference | 17th European Symposium on Computer Aided Process Engineering |
|---|---|
| Number | 17 |
| Country | Romania |
| City | Bucharest |
| Period | 27-05-07 → 30-05-07 |
| Sponsor | Univ Bucharest; Univ Cluj Napoca |
| Internet address | http://www.escape17.upb.ro/index.htm |
| Name | Computer Aided Chemical Engineering |
|---|
| Citations | Web of Science® Times Cited: No match on DOI |
|---|
Keywords
- Covariance Estimation, State estimation, Kalman filter
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