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School / Prep
ENSEIRB-MATMECA
Internal code
EE9AU305
Description
The aim of this course is to present Kalman filtering, which is based on a representation of the system in state space (REE) that can be linear or non-linear. To this end, the way in which the REE is obtained is first explained, using several examples to highlight the linear or non-linear character. This is followed by Kalman filtering, which estimates the state vector from the information available on the system. The linear case is detailed, then the non-linear case is tackled using the extended Kalman filter. A matlab illustration is provided.
Teaching hours
- CMLectures8h
Further information
Automatic
Assessment of knowledge
Initial assessment / Main session
| Type of assessment | Nature of assessment | Duration (in minutes) | Number of tests | Evaluation coefficient | Eliminatory evaluation mark | Remarks |
|---|---|---|---|---|---|---|
| Final inspection | Written | 60 | 1 | without document |
Second chance / Catch-up session
| Type of assessment | Nature of assessment | Duration (in minutes) | Number of tests | Evaluation coefficient | Eliminatory evaluation mark | Remarks |
|---|---|---|---|---|---|---|
| Final test | Written | 60 | 1 | without document |